Publications

This bibliography is extracted from various primary sources using automatic language understanding tools. A good faith effort has been made to eliminate errors and minimize omissions. Please bring any remaining errors or omissions to the attention of CLSP by writing to [email protected].

Kartik Narayan, VS Vibashan, R. Chellappa, and Vishal M. Patel, “FaceXFormer: A Unified Transformer for Facial Analysis.” 2024.
[BibTeX] [Link]

@inproceedings{268532373,
title = {FaceXFormer: A Unified Transformer for Facial Analysis},
author = {{Kartik Narayan} and {VS Vibashan} and {R. Chellappa} and {Vishal M. Patel}},
year = 2024,
month = {3},
booktitle = {},
url = {https://www.semanticscholar.org/paper/cf9ea0a2ae56bce6d2fdbc9f81633ef8ce9df59c},
}

Sonal Joshi, Thomas Thebaud, J. Villalba, and N. Dehak, “Unraveling Adversarial Examples against Speaker Identification – Techniques for Attack Detection and Victim Model Classification,” in arXiv.org, 2024.
[BibTeX] [Link]

@inproceedings{268091248,
title = {Unraveling Adversarial Examples against Speaker Identification - Techniques for Attack Detection and Victim Model Classification},
author = {{Sonal Joshi} and {Thomas Thebaud} and {J. Villalba} and {N. Dehak}},
year = 2024,
month = {2},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/af87c6786c1e7f8345f3c5768668617df6cc2771},
}

Peter Abadir, Esther S Oh, Rama Chellappa, N. Choudhry, George Demiris, Deepak Ganesan, Jason Karlawish, Benjamin M. Marlin, Rose M Li, N. Dehak, Alicia Arbaje, Mathias Unberath, Thomas Cudjoe, Christopher Chute, Jason H Moore, Phillip Phan, Quincy M. Samus, Nancy L. Schoenborn, Alexis Battle, and Jeremy D Walston, “Artificial Intelligence and Technology Collaboratories: Innovating aging research and Alzheimer’s care.,” in Alzheimer’s & Dementia, 2024.
[BibTeX] [Link]

@inproceedings{267522236,
title = {Artificial Intelligence and Technology Collaboratories: Innovating aging research and Alzheimer's care.},
author = {{Peter Abadir} and {Esther S Oh} and {Rama Chellappa} and {N. Choudhry} and {George Demiris} and {Deepak Ganesan} and {Jason Karlawish} and {Benjamin M. Marlin} and {Rose M Li} and {N. Dehak} and {Alicia Arbaje} and {Mathias Unberath} and {Thomas Cudjoe} and {Christopher Chute} and {Jason H Moore} and {Phillip Phan} and {Quincy M. Samus} and {Nancy L. Schoenborn} and {Alexis Battle} and {Jeremy D Walston}},
year = 2024,
month = {2},
booktitle = {Alzheimer's & Dementia},
url = {https://www.semanticscholar.org/paper/893d9dc2d86b71e3ba67490decd96f91954e47ce},
}

Deming Li, A. Butala, L. Moro-Velázquez, Trevor Meyer, Esther S. Oh, Chelsey Motley, J. Villalba, and N. Dehak, “Automating the analysis of eye movement for different neurodegenerative disorders,” in Comput. Biol. Medicine, 2024.
[BibTeX] [Link]

@inproceedings{266798865,
title = {Automating the analysis of eye movement for different neurodegenerative disorders},
author = {{Deming Li} and {A. Butala} and {L. Moro-Velázquez} and {Trevor Meyer} and {Esther S. Oh} and {Chelsey Motley} and {J. Villalba} and {N. Dehak}},
year = 2024,
month = {1},
booktitle = {Comput. Biol. Medicine},
url = {https://www.semanticscholar.org/paper/f375c9d0a595152ff21f96a0a5606c7d033548f3},
}

Saurabhchand Bhati, J. Villalba, Piotr Żelasko, L. Moro-Velázquez, and N. Dehak, “Slowness Regularized Contrastive Predictive Coding for Acoustic Unit Discovery,” in IEEE/ACM Transactions on Audio Speech and Language Processing, 2024.
[BibTeX] [Link]

@inproceedings{267144330,
title = {Slowness Regularized Contrastive Predictive Coding for Acoustic Unit Discovery},
author = {{Saurabhchand Bhati} and {J. Villalba} and {Piotr Żelasko} and {L. Moro-Velázquez} and {N. Dehak}},
year = 2024,
booktitle = {IEEE/ACM Transactions on Audio Speech and Language Processing},
url = {https://www.semanticscholar.org/paper/1748de2018438a1015f557ed72424602b144f5ba},
}

A. Favaro, N. Dehak, Thomas Thebaud, Esther S Oh, and L. Moro-Velázquez, “Evaluation of Interpretable Speech Biomarkers for Monitoring Alzheimer’s Disease and Mild Cognitive Impairment Progression,” in Alzheimer’s & Dementia, 2023.
[BibTeX] [Link]

@inproceedings{266523165,
title = {Evaluation of Interpretable Speech Biomarkers for Monitoring Alzheimer’s Disease and Mild Cognitive Impairment Progression},
author = {{A. Favaro} and {N. Dehak} and {Thomas Thebaud} and {Esther S Oh} and {L. Moro-Velázquez}},
year = 2023,
month = {12},
booktitle = {Alzheimer's & Dementia},
url = {https://www.semanticscholar.org/paper/3434b5755b9c8bdb4250cabaabad655aee402440},
}

@inproceedings{266523081,
title = {Evaluation of Interpretable Speech Biomarkers for Monitoring Alzheimer’s Disease and Mild Cognitive Impairment Progression},
author = {{A. Favaro} and {N. Dehak} and {Thomas Thebaud} and {Esther S Oh} and {L. Moro-Velázquez}},
year = 2023,
month = {12},
booktitle = {Alzheimer's & Dementia},
url = {https://www.semanticscholar.org/paper/2f88f04aeb6eb8cac8c5706c294bcd3045faa966},
}

Maliha Jahan, L. Moro-Velázquez, Thomas Thebaud, N. Dehak, and J. Villalba, “Model-Based Fairness Metric for Speaker Verification,” in Automatic Speech Recognition & Understanding, 2023.
[BibTeX] [Link]

@inproceedings{267043424,
title = {Model-Based Fairness Metric for Speaker Verification},
author = {{Maliha Jahan} and {L. Moro-Velázquez} and {Thomas Thebaud} and {N. Dehak} and {J. Villalba}},
year = 2023,
month = {12},
booktitle = {Automatic Speech Recognition & Understanding},
url = {https://www.semanticscholar.org/paper/f308fc3883c5a18c050b44ec932b59067dfd83f3},
}

Deming Li, Trevor Meyer, Esther S Oh, A. Butala, N. Dehak, and L. Moro-Velázquez, “Multi‐task analysis of oculographic biomarkers to evaluate motoric and cognitive patterns in Alzheimer’s Disease,” in Alzheimer’s & Dementia, 2023.
[BibTeX] [Link]

@inproceedings{266523855,
title = {Multi‐task analysis of oculographic biomarkers to evaluate motoric and cognitive patterns in Alzheimer’s Disease},
author = {{Deming Li} and {Trevor Meyer} and {Esther S Oh} and {A. Butala} and {N. Dehak} and {L. Moro-Velázquez}},
year = 2023,
month = {12},
booktitle = {Alzheimer's & Dementia},
url = {https://www.semanticscholar.org/paper/c2f99d03369b3583618c774b58c871c9707724bb},
}

Martin Sustek, Sonal Joshi, Henry Li, Thomas Thebaud, J. Villalba, S. Khudanpur, and N. Dehak, “Joint Energy-Based Model for Robust Speech Classification System Against Dirty-Label Backdoor Poisoning Attacks,” in Automatic Speech Recognition & Understanding, 2023.
[BibTeX] [Link]

@inproceedings{267044159,
title = {Joint Energy-Based Model for Robust Speech Classification System Against Dirty-Label Backdoor Poisoning Attacks},
author = {{Martin Sustek} and {Sonal Joshi} and {Henry Li} and {Thomas Thebaud} and {J. Villalba} and {S. Khudanpur} and {N. Dehak}},
year = 2023,
month = {12},
booktitle = {Automatic Speech Recognition & Understanding},
url = {https://www.semanticscholar.org/paper/1fd003bf9de393bcddbda63b738b71ced6203802},
}

Thomas Thebaud, Casey Chen, L. Moro-Velázquez, N. Dehak, and Esther S Oh, “Handwriting characteristics analysis for Alzheimer’s Disease and Mild Cognitive Impairments Assessment,” in Alzheimer’s & Dementia, 2023.
[BibTeX] [Link]

@inproceedings{266523924,
title = {Handwriting characteristics analysis for Alzheimer’s Disease and Mild Cognitive Impairments Assessment},
author = {{Thomas Thebaud} and {Casey Chen} and {L. Moro-Velázquez} and {N. Dehak} and {Esther S Oh}},
year = 2023,
month = {12},
booktitle = {Alzheimer's & Dementia},
url = {https://www.semanticscholar.org/paper/b6ffb09dbe20a54ddb5f3e6f3a319f482bb3c0aa},
}

Thomas Thebaud, Sonal Joshi, Henry Li, Martin Sustek, J. Villalba, S. Khudanpur, and N. Dehak, “Clustering Unsupervised Representations as Defense Against Poisoning Attacks on Speech Commands Classification System,” in Automatic Speech Recognition & Understanding, 2023.
[BibTeX] [Link]

@inproceedings{267043595,
title = {Clustering Unsupervised Representations as Defense Against Poisoning Attacks on Speech Commands Classification System},
author = {{Thomas Thebaud} and {Sonal Joshi} and {Henry Li} and {Martin Sustek} and {J. Villalba} and {S. Khudanpur} and {N. Dehak}},
year = 2023,
month = {12},
booktitle = {Automatic Speech Recognition & Understanding},
url = {https://www.semanticscholar.org/paper/d59282b7adbdd1aef7754309aa72e98598059c1a},
}

Y. Wang, L. Moro-Velázquez, A. Favaro, D. Li, E. Oh, A. Butala, J. Villalba, and N. Dehak, “Binocular Discoordination Kinetic Features: A Novel Approach to Evaluate Neurodegenerative Diseases,” in IEEE Signal Processing in Medicine and Biology Symposium, 2023.
[BibTeX] [Link]

@inproceedings{266602177,
title = {Binocular Discoordination Kinetic Features: A Novel Approach to Evaluate Neurodegenerative Diseases},
author = {{Y. Wang} and {L. Moro-Velázquez} and {A. Favaro} and {D. Li} and {E. Oh} and {A. Butala} and {J. Villalba} and {N. Dehak}},
year = 2023,
month = {12},
booktitle = {IEEE Signal Processing in Medicine and Biology Symposium},
url = {https://www.semanticscholar.org/paper/306f3684946774ed21ddba490c0f120f02a5421a},
}

@inproceedings{266522904,
title = {Multi‐task analysis of oculographic biomarkers to evaluate motoric and cognitive patterns in Alzheimer’s Disease},
author = {{Deming Li} and {Trevor Meyer} and {Esther S Oh} and {A. Butala} and {N. Dehak} and {L. Moro-Velázquez}},
year = 2023,
month = {12},
booktitle = {Alzheimer's & Dementia},
url = {https://www.semanticscholar.org/paper/d958ba9662d442878a1d1d11d4e0968e6df42e4d},
}

@inproceedings{266522435,
title = {Handwriting characteristics analysis for Alzheimer’s Disease and Mild Cognitive Impairments Assessment},
author = {{Thomas Thebaud} and {Casey Chen} and {L. Moro-Velázquez} and {N. Dehak} and {Esther S Oh}},
year = 2023,
month = {12},
booktitle = {Alzheimer's & Dementia},
url = {https://www.semanticscholar.org/paper/65b786c68cef24ed41374bd9f279617d694e2dd4},
}

W. Tan, C. Lin, and J. Eisner, “Structure-Aware Path Inference for Neural Finite State Transducers,” in Proceedings of the NeurIPS 2023 Workshop “I Can’t Believe It’s Not Better: Failure Modes in the Age of Foundation Models”, 2023.
[BibTeX] [Link]

@InProceedings{tan-et-al-2023,
author = "Weiting Tan and Chu-Cheng Lin and Jason Eisner",
title = "Structure-Aware Path Inference for Neural Finite State
Transducers",
booktitle = "Proceedings of the {NeurIPS} 2023 Workshop ``{I}
Can’t Believe It’s Not Better: Failure Modes in the
Age of Foundation Models''",
year = "2023",
month = dec,
URL = "http://cs.jhu.edu/~jason/papers/#tan-et-al-2023",
}

S. Roy, S. Thomson, T. Chen, R. Shin, A. Pauls, J. Eisner, and B. V. Durme, “BenchCLAMP: A Benchmark for Evaluating Language Models on Syntactic and Semantic Parsing,” in Proceedings of the Thirty-Seventh Conference on Neural Information Processing Systems, 2023.
[BibTeX] [Link]

@InProceedings{roy-et-al-2023,
author = "Subhro Roy and Sam Thomson and Tongfei Chen and
Richard Shin and Adam Pauls and Jason Eisner and
Benjamin Van Durme",
title = "{BenchCLAMP}: {A} Benchmark for Evaluating Language
Models on Syntactic and Semantic Parsing",
booktitle = "Proceedings of the Thirty-Seventh Conference on Neural
Information Processing Systems",
note = "Datasets and Benchmarks Track",
year = "2023",
month = dec,
URL = "http://cs.jhu.edu/~jason/papers/#roy-et-al-2023",
}

R. Zhong, C. Snell, D. Klein, and Jason Eisner, “Non-Programmers Can Label Programs Indirectly via Active Examples: A Case Study with Text-to-SQL,” in Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023, p. 5126–5152.
[BibTeX] [Link]

@InProceedings{zhong-et-al-2023,
aclid = "2023.emnlp-main.312",
author = "Ruiqi Zhong and Charlie Snell and Dan Klein and Jason
Eisner",
title = "Non-Programmers Can Label Programs Indirectly via
Active Examples: {A} Case Study with Text-to-{SQL}",
booktitle = "Proceedings of the 2023 Conference on Empirical
Methods in Natural Language Processing",
pages = "5126--5152",
year = "2023",
month = dec,
URL = "http://cs.jhu.edu/~jason/papers/#zhong-et-al-2023",
}

Trevor Meyer, Camden Shultz, N. Dehak, L. Moro-Velázquez, and Pedro P. Irazoqui, “Time Scale Network: A Shallow Neural Network For Time Series Data,” in arXiv.org, 2023.
[BibTeX] [Link]

@inproceedings{265128667,
title = {Time Scale Network: A Shallow Neural Network For Time Series Data},
author = {{Trevor Meyer} and {Camden Shultz} and {N. Dehak} and {L. Moro-Velázquez} and {Pedro P. Irazoqui}},
year = 2023,
month = {11},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/deacbb4906e1d2e597602a65b434a8132953ad8d},
}

Jiarui Hai, Helin Wang, Dongchao Yang, Karan Thakkar, N. Dehak, and Mounya Elhilali, “DPM-TSE: A Diffusion Probabilistic Model for Target Sound Extraction,” in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2023.
[BibTeX] [Link]

@inproceedings{263830793,
title = {DPM-TSE: A Diffusion Probabilistic Model for Target Sound Extraction},
author = {{Jiarui Hai} and {Helin Wang} and {Dongchao Yang} and {Karan Thakkar} and {N. Dehak} and {Mounya Elhilali}},
year = 2023,
month = {10},
booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
url = {https://www.semanticscholar.org/paper/70aec6486668cc5ca25d45240c68de223a8deda7},
}

S. Sia and K. Duh, “In-context Learning as Maintaining Coherency: A Study of On-the-fly Machine Translation Using Large Language Models,” in Proceedings of Machine Translation Summit XIX, Vol. 1: Research Track, Macau SAR, China, 2023, p. 173–185.
[BibTeX] [Abstract] [Link]

The phenomena of in-context learning has typically been thought of as {“}learning from examples{”}. In this work which focuses on Machine Translation, we present a perspective of in-context learning as the desired generation task maintaining coherency with its context, i.e., the prompt examples. We first investigate randomly sampled prompts across 4 domains, and find that translation performance improves when shown in-domain prompts. Next, we investigate coherency for the in-domain setting, which uses prompt examples from a moving window. We study this with respect to other factors that have previously been identified in the literature such as length, surface similarity and sentence embedding similarity. Our results across 3 models (GPTNeo2.7B, Bloom3B, XGLM2.9B), and three translation directions (en$\rightarrow${pt, de, fr}) suggest that the long-term coherency of the prompts and the test sentence is a good indicator of downstream translation performance. In doing so, we demonstrate the efficacy of in-context Machine Translation for on-the-fly adaptation.

@inproceedings{sia-duh-2023-context,
title = "In-context Learning as Maintaining Coherency: A Study of On-the-fly Machine Translation Using Large Language Models",
author = "Sia, Suzanna and
Duh, Kevin",
editor = "Utiyama, Masao and
Wang, Rui",
booktitle = "Proceedings of Machine Translation Summit XIX, Vol. 1: Research Track",
month = sep,
year = "2023",
address = "Macau SAR, China",
publisher = "Asia-Pacific Association for Machine Translation",
url = "https://aclanthology.org/2023.mtsummit-research.15",
pages = "173--185",
abstract = "The phenomena of in-context learning has typically been thought of as {``}learning from examples{''}. In this work which focuses on Machine Translation, we present a perspective of in-context learning as the desired generation task maintaining coherency with its context, i.e., the prompt examples. We first investigate randomly sampled prompts across 4 domains, and find that translation performance improves when shown in-domain prompts. Next, we investigate coherency for the in-domain setting, which uses prompt examples from a moving window. We study this with respect to other factors that have previously been identified in the literature such as length, surface similarity and sentence embedding similarity. Our results across 3 models (GPTNeo2.7B, Bloom3B, XGLM2.9B), and three translation directions (en$\rightarrow${pt, de, fr}) suggest that the long-term coherency of the prompts and the test sentence is a good indicator of downstream translation performance. In doing so, we demonstrate the efficacy of in-context Machine Translation for on-the-fly adaptation.",
}

J. Chi, B. Lu, J. Eisner, P. Bell, P. Jyothi, and A. M. Ali, “Unsupervised Code-Switched Text Generation from Parallel Text,” in Proceedings of INTERSPEECH, Dublin, 2023.
[BibTeX] [Link]

@InProceedings{chi-et-al-2023,
author = "Jie Chi and Brian Lu and Jason Eisner and Peter Bell
and Preethi Jyothi and Ahmed M. Ali",
title = "Unsupervised Code-Switched Text Generation from
Parallel Text",
booktitle = "Proceedings of INTERSPEECH",
year = "2023",
month = aug,
address = "Dublin",
URL = "http://cs.jhu.edu/~jason/papers/#chi-et-al-2023",
}

G. Portillo Wightman, A. Delucia, and M. Dredze, “Strength in Numbers: Estimating Confidence of Large Language Models by Prompt Agreement,” in Proceedings of the 3rd Workshop on Trustworthy Natural Language Processing (TrustNLP 2023), Toronto, Canada, 2023, p. 326–362. doi:10.18653/v1/2023.trustnlp-1.28
[BibTeX] [Abstract] [Link]

Large language models have achieved impressive few-shot performance on a wide variety of tasks. However, in many settings, users require confidence estimates for model predictions. While traditional classifiers produce scores for each label, language models instead produce scores for the generation which may not be well calibrated. We compare generations across diverse prompts and show that these can be used to create confidence scores. By utilizing more prompts we can get more precise confidence estimates and use response diversity as a proxy for confidence. We evaluate this approach across ten multiple-choice question-answering datasets using three models: T0, FLAN-T5, and GPT-3. In addition to analyzing multiple human written prompts, we automatically generate more prompts using a language model in order to produce finer-grained confidence estimates. Our method produces more calibrated confidence estimates compared to the log probability of the answer to a single prompt. These improvements could benefit users who rely on prediction confidence for integration into a larger system or in decision-making processes.

@inproceedings{portillo-wightman-etal-2023-strength,
title = "Strength in Numbers: Estimating Confidence of Large Language Models by Prompt Agreement",
author = "Portillo Wightman, Gwenyth and
Delucia, Alexandra and
Dredze, Mark",
editor = "Ovalle, Anaelia and
Chang, Kai-Wei and
Mehrabi, Ninareh and
Pruksachatkun, Yada and
Galystan, Aram and
Dhamala, Jwala and
Verma, Apurv and
Cao, Trista and
Kumar, Anoop and
Gupta, Rahul",
booktitle = "Proceedings of the 3rd Workshop on Trustworthy Natural Language Processing (TrustNLP 2023)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.trustnlp-1.28",
doi = "10.18653/v1/2023.trustnlp-1.28",
pages = "326--362",
abstract = "Large language models have achieved impressive few-shot performance on a wide variety of tasks. However, in many settings, users require confidence estimates for model predictions. While traditional classifiers produce scores for each label, language models instead produce scores for the generation which may not be well calibrated. We compare generations across diverse prompts and show that these can be used to create confidence scores. By utilizing more prompts we can get more precise confidence estimates and use response diversity as a proxy for confidence. We evaluate this approach across ten multiple-choice question-answering datasets using three models: T0, FLAN-T5, and GPT-3. In addition to analyzing multiple human written prompts, we automatically generate more prompts using a language model in order to produce finer-grained confidence estimates. Our method produces more calibrated confidence estimates compared to the log probability of the answer to a single prompt. These improvements could benefit users who rely on prediction confidence for integration into a larger system or in decision-making processes.",
}

X. Zhang, K. Duh, and P. McNamee, “A Hyperparameter Optimization Toolkit for Neural Machine Translation Research,” in Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations), Toronto, Canada, 2023, p. 161–168. doi:10.18653/v1/2023.acl-demo.15
[BibTeX] [Abstract] [Link]

Hyperparameter optimization is an important but often overlooked process in the research of deep learning technologies. To obtain a good model, one must carefully tune hyperparameters that determine the architecture and training algorithm. Insufficient tuning may result in poor results, while inequitable tuning may lead to exaggerated differences between models. We present a hyperparameter optimization toolkit for neural machine translation (NMT) to help researchers focus their time on the creative rather than the mundane. The toolkit is implemented as a wrapper on top of the open-source Sockeye NMT software. Using the Asynchronous Successive Halving Algorithm (ASHA), we demonstrate that it is possible to discover near-optimal models under a computational budget with little effort. Code: \url{https://github.com/kevinduh/sockeye-recipes3Video} demo: \url{https://cs.jhu.edu/kevinduh/j/demo.mp4}

@inproceedings{zhang-etal-2023-hyperparameter,
title = "A Hyperparameter Optimization Toolkit for Neural Machine Translation Research",
author = "Zhang, Xuan and
Duh, Kevin and
McNamee, Paul",
editor = "Bollegala, Danushka and
Huang, Ruihong and
Ritter, Alan",
booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.acl-demo.15",
doi = "10.18653/v1/2023.acl-demo.15",
pages = "161--168",
abstract = "Hyperparameter optimization is an important but often overlooked process in the research of deep learning technologies. To obtain a good model, one must carefully tune hyperparameters that determine the architecture and training algorithm. Insufficient tuning may result in poor results, while inequitable tuning may lead to exaggerated differences between models. We present a hyperparameter optimization toolkit for neural machine translation (NMT) to help researchers focus their time on the creative rather than the mundane. The toolkit is implemented as a wrapper on top of the open-source Sockeye NMT software. Using the Asynchronous Successive Halving Algorithm (ASHA), we demonstrate that it is possible to discover near-optimal models under a computational budget with little effort. Code: \url{https://github.com/kevinduh/sockeye-recipes3Video} demo: \url{https://cs.jhu.edu/kevinduh/j/demo.mp4}",
}

M. Agarwal, S. Agrawal, A. Anastasopoulos, L. Bentivogli, O. Bojar, C. Borg, M. Carpuat, R. Cattoni, M. Cettolo, M. Chen, W. Chen, K. Choukri, A. Chronopoulou, A. Currey, T. Declerck, Q. Dong, K. Duh, Y. Estève, M. Federico, S. Gahbiche, B. Haddow, B. Hsu, P. Mon Htut, H. Inaguma, D. Javorský, J. Judge, Y. Kano, T. Ko, R. Kumar, P. Li, X. Ma, P. Mathur, E. Matusov, P. McNamee, J. P. McCrae, K. Murray, M. Nadejde, S. Nakamura, M. Negri, H. Nguyen, J. Niehues, X. Niu, A. Kr. Ojha, J. E. Ortega, P. Pal, J. Pino, L. van der Plas, P. Polák, E. Rippeth, E. Salesky, J. Shi, M. Sperber, S. Stüker, K. Sudoh, Y. Tang, B. Thompson, K. Tran, M. Turchi, A. Waibel, M. Wang, S. Watanabe, and R. Zevallos, “FINDINGS OF THE IWSLT 2023 EVALUATION CAMPAIGN,” in Proceedings of the 20th International Conference on Spoken Language Translation (IWSLT 2023), Toronto, Canada (in-person and online), 2023, p. 1–61. doi:10.18653/v1/2023.iwslt-1.1
[BibTeX] [Abstract] [Link]

This paper reports on the shared tasks organized by the 20th IWSLT Conference. The shared tasks address 9 scientific challenges in spoken language translation: simultaneous and offline translation, automatic subtitling and dubbing, speech-to-speech translation, multilingual, dialect and low-resource speech translation, and formality control. The shared tasks attracted a total of 38 submissions by 31 teams. The growing interest towards spoken language translation is also witnessed by the constantly increasing number of shared task organizers and contributors to the overview paper, almost evenly distributed across industry and academia.

@inproceedings{agrawal-etal-2023-findings,
title = "{FINDINGS} {OF} {THE} {IWSLT} 2023 {EVALUATION} {CAMPAIGN}",
author = {Agarwal, Milind and
Agrawal, Sweta and
Anastasopoulos, Antonios and
Bentivogli, Luisa and
Bojar, Ond{\v{r}}ej and
Borg, Claudia and
Carpuat, Marine and
Cattoni, Roldano and
Cettolo, Mauro and
Chen, Mingda and
Chen, William and
Choukri, Khalid and
Chronopoulou, Alexandra and
Currey, Anna and
Declerck, Thierry and
Dong, Qianqian and
Duh, Kevin and
Est{\`e}ve, Yannick and
Federico, Marcello and
Gahbiche, Souhir and
Haddow, Barry and
Hsu, Benjamin and
Mon Htut, Phu and
Inaguma, Hirofumi and
Javorsk{\'y}, D{\'a}vid and
Judge, John and
Kano, Yasumasa and
Ko, Tom and
Kumar, Rishu and
Li, Pengwei and
Ma, Xutai and
Mathur, Prashant and
Matusov, Evgeny and
McNamee, Paul and
P. McCrae, John and
Murray, Kenton and
Nadejde, Maria and
Nakamura, Satoshi and
Negri, Matteo and
Nguyen, Ha and
Niehues, Jan and
Niu, Xing and
Kr. Ojha, Atul and
E. Ortega, John and
Pal, Proyag and
Pino, Juan and
van der Plas, Lonneke and
Pol{\'a}k, Peter and
Rippeth, Elijah and
Salesky, Elizabeth and
Shi, Jiatong and
Sperber, Matthias and
St{\"u}ker, Sebastian and
Sudoh, Katsuhito and
Tang, Yun and
Thompson, Brian and
Tran, Kevin and
Turchi, Marco and
Waibel, Alex and
Wang, Mingxuan and
Watanabe, Shinji and
Zevallos, Rodolfo},
editor = "Salesky, Elizabeth and
Federico, Marcello and
Carpuat, Marine",
booktitle = "Proceedings of the 20th International Conference on Spoken Language Translation (IWSLT 2023)",
month = jul,
year = "2023",
address = "Toronto, Canada (in-person and online)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.iwslt-1.1",
doi = "10.18653/v1/2023.iwslt-1.1",
pages = "1--61",
abstract = "This paper reports on the shared tasks organized by the 20th IWSLT Conference. The shared tasks address 9 scientific challenges in spoken language translation: simultaneous and offline translation, automatic subtitling and dubbing, speech-to-speech translation, multilingual, dialect and low-resource speech translation, and formality control. The shared tasks attracted a total of 38 submissions by 31 teams. The growing interest towards spoken language translation is also witnessed by the constantly increasing number of shared task organizers and contributors to the overview paper, almost evenly distributed across industry and academia.",
}

E. Spaulding, G. Kazantsev, and M. Dredze, “Joint End-to-end Semantic Proto-role Labeling,” in Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), Toronto, Canada, 2023, p. 723–736. doi:10.18653/v1/2023.acl-short.63
[BibTeX] [Abstract] [Link]

Semantic proto-role labeling (SPRL) assigns properties to arguments based on a series of binary labels. While multiple studies have evaluated various approaches to SPRL, it has only been studied in-depth as a standalone task using gold predicate/argument pairs. How do SPRL systems perform as part of an information extraction pipeline? We model SPRL jointly with predicate-argument extraction using a deep transformer model. We find that proto-role labeling is surprisingly robust in this setting, with only a small decrease when using predicted arguments. We include a detailed analysis of each component of the joint system, and an error analysis to understand correlations in errors between system stages. Finally, we study the effects of annotation errors on SPRL.

@inproceedings{spaulding-etal-2023-joint,
title = "Joint End-to-end Semantic Proto-role Labeling",
author = "Spaulding, Elizabeth and
Kazantsev, Gary and
Dredze, Mark",
editor = "Rogers, Anna and
Boyd-Graber, Jordan and
Okazaki, Naoaki",
booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.acl-short.63",
doi = "10.18653/v1/2023.acl-short.63",
pages = "723--736",
abstract = "Semantic proto-role labeling (SPRL) assigns properties to arguments based on a series of binary labels. While multiple studies have evaluated various approaches to SPRL, it has only been studied in-depth as a standalone task using gold predicate/argument pairs. How do SPRL systems perform as part of an information extraction pipeline? We model SPRL jointly with predicate-argument extraction using a deep transformer model. We find that proto-role labeling is surprisingly robust in this setting, with only a small decrease when using predicted arguments. We include a detailed analysis of each component of the joint system, and an error analysis to understand correlations in errors between system stages. Finally, we study the effects of annotation errors on SPRL.",
}

J. Gwinnup, T. Anderson, B. Ore, E. Hansen, and K. Duh, “Enhancing Video Translation Context with Object Labels,” in Proceedings of the 20th International Conference on Spoken Language Translation (IWSLT 2023), Toronto, Canada (in-person and online), 2023, p. 130–137. doi:10.18653/v1/2023.iwslt-1.8
[BibTeX] [Abstract] [Link]

We present a simple yet efficient method to enhance the quality of machine translation models trained on multimodal corpora by augmenting the training text with labels of detected objects in the corresponding video segments. We then test the effects of label augmentation in both baseline and two automatic speech recognition (ASR) conditions. In contrast with multimodal techniques that merge visual and textual features, our modular method is easy to implement and the results are more interpretable. Comparisons are made with Transformer translation architectures trained with baseline and augmented labels, showing improvements of up to +1.0 BLEU on the How2 dataset.

@inproceedings{gwinnup-etal-2023-enhancing,
title = "Enhancing Video Translation Context with Object Labels",
author = "Gwinnup, Jeremy and
Anderson, Tim and
Ore, Brian and
Hansen, Eric and
Duh, Kevin",
editor = "Salesky, Elizabeth and
Federico, Marcello and
Carpuat, Marine",
booktitle = "Proceedings of the 20th International Conference on Spoken Language Translation (IWSLT 2023)",
month = jul,
year = "2023",
address = "Toronto, Canada (in-person and online)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.iwslt-1.8",
doi = "10.18653/v1/2023.iwslt-1.8",
pages = "130--137",
abstract = "We present a simple yet efficient method to enhance the quality of machine translation models trained on multimodal corpora by augmenting the training text with labels of detected objects in the corresponding video segments. We then test the effects of label augmentation in both baseline and two automatic speech recognition (ASR) conditions. In contrast with multimodal techniques that merge visual and textual features, our modular method is easy to implement and the results are more interpretable. Comparisons are made with Transformer translation architectures trained with baseline and augmented labels, showing improvements of up to +1.0 BLEU on the How2 dataset.",
}

S. Zhang, S. Wu, O. Irsoy, S. Lu, M. Bansal, M. Dredze, and D. Rosenberg, “MixCE: Training Autoregressive Language Models by Mixing Forward and Reverse Cross-Entropies,” in Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Toronto, Canada, 2023, p. 9027–9050. doi:10.18653/v1/2023.acl-long.502
[BibTeX] [Abstract] [Link]

Autoregressive language models are trained by minimizing the cross-entropy of the model distribution Q relative to the data distribution P {–} that is, minimizing the forward cross-entropy, which is equivalent to maximum likelihood estimation (MLE). We have observed that models trained in this way may {“}over-generalize{”}, in the sense that they produce non-human-like text. Moreover, we believe that reverse cross-entropy, i.e., the cross-entropy of P relative to Q, is a better reflection of how a human would evaluate text generated by a model. Hence, we propose learning with MixCE, an objective that mixes the forward and reverse cross-entropies. We evaluate models trained with this objective on synthetic data settings (where P is known) and real data, and show that the resulting models yield better generated text without complex decoding strategies.

@inproceedings{zhang-etal-2023-mixce,
title = "{M}ix{CE}: Training Autoregressive Language Models by Mixing Forward and Reverse Cross-Entropies",
author = "Zhang, Shiyue and
Wu, Shijie and
Irsoy, Ozan and
Lu, Steven and
Bansal, Mohit and
Dredze, Mark and
Rosenberg, David",
editor = "Rogers, Anna and
Boyd-Graber, Jordan and
Okazaki, Naoaki",
booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.acl-long.502",
doi = "10.18653/v1/2023.acl-long.502",
pages = "9027--9050",
abstract = "Autoregressive language models are trained by minimizing the cross-entropy of the model distribution Q relative to the data distribution P {--} that is, minimizing the forward cross-entropy, which is equivalent to maximum likelihood estimation (MLE). We have observed that models trained in this way may {``}over-generalize{''}, in the sense that they produce non-human-like text. Moreover, we believe that reverse cross-entropy, i.e., the cross-entropy of P relative to Q, is a better reflection of how a human would evaluate text generated by a model. Hence, we propose learning with MixCE, an objective that mixes the forward and reverse cross-entropies. We evaluate models trained with this objective on synthetic data settings (where P is known) and real data, and show that the resulting models yield better generated text without complex decoding strategies.",
}

H. Fang, A. Balakrishnan, H. Jhamtani, J. Bufe, J. Crawford, Jayant Krishnamurthy, A. Pauls, J. Eisner, Jacob Andreas, and D. Klein, “The Whole Truth and Nothing But the Truth: Faithful and Controllable Dialogue Response Generation with Dataflow Transduction and Constrained Decoding,” in Findings of the Association for Computational Linguistics: ACL 2023, 2023, p. 5682–5700.
[BibTeX] [Link]

@InProceedings{fang-et-al-2023,
author = "Hao Fang and Anusha Balakrishnan and Harsh Jhamtani
and John Bufe and Jean Crawford and Jayant
Krishnamurthy and Adam Pauls and Jason Eisner and Jacob
Andreas and Dan Klein",
title = "The Whole Truth and Nothing But the Truth: Faithful
and Controllable Dialogue Response Generation with
Dataflow Transduction and Constrained Decoding",
booktitle = "Findings of the Association for Computational
Linguistics: ACL 2023",
year = "2023",
month = jul,
pages = "5682--5700",
URL = "http://cs.jhu.edu/~jason/papers/#fang-et-al-2023",
}

B. Z. Li, J. Eisner, A. Pauls, and Sam Thomson, “Toward Interactive Dictation,” in Proceedings of the Association for Computational Linguistics (ACL), 2023, p. 15319–15338.
[BibTeX] [Link]

@InProceedings{li-et-al-2023-dictation,
author = "Belinda Z. Li and Jason Eisner and Adam Pauls and Sam
Thomson",
title = "Toward Interactive Dictation",
booktitle = "Proceedings of the Association for Computational
Linguistics (ACL)",
year = "2023",
month = jul,
pages = "15319--15338",
URL = "http://cs.jhu.edu/~jason/papers/#li-et-al-2023-dictation",
}

F. Mireshghallah, Y. Su, Tatsunori Hashimoto, J. Eisner, and R. Shin, “Privacy-Preserving Domain Adaptation of Semantic Parsers,” in Proceedings of the Association for Computational Linguistics (ACL), 2023, p. 4950–4970.
[BibTeX] [Link]

@InProceedings{mireshghallah-et-al-2023,
author = "Fatemehsadat Mireshghallah and Yu Su and Tatsunori
Hashimoto and Jason Eisner and Richard Shin",
title = "Privacy-Preserving Domain Adaptation of Semantic
Parsers",
booktitle = "Proceedings of the Association for Computational
Linguistics (ACL)",
year = "2023",
month = jul,
pages = "4950--4970",
URL = "http://cs.jhu.edu/~jason/papers/#mireshghallah-et-al-2023",
}

X. L. Li, A. Holtzman, D. Fried, P. Liang, J. Eisner, T. Hashimoto, L. Zettlemoyer, and M. Lewis, “Contrastive Decoding: Open-ended Text Generation as Optimization,” in Proceedings of the Association for Computational Linguistics (ACL), 2023, p. 12286–12312.
[BibTeX] [Link]

@InProceedings{li-et-al-2023-cd,
author = "Xiang Lisa Li and Ari Holtzman and Daniel Fried and
Percy Liang and Jason Eisner and Tatsunori Hashimoto
and Luke Zettlemoyer and Mike Lewis",
title = "Contrastive Decoding: Open-ended Text Generation as
Optimization",
booktitle = "Proceedings of the Association for Computational
Linguistics (ACL)",
year = "2023",
month = jul,
pages = "12286--12312",
URL = "http://cs.jhu.edu/~jason/papers/#li-et-al-2023-cd",
}

L. Du, L. T. Hennigen, T. Pimentel, C. Meister, J. Eisner, and R. Cotterell, “A Measure-Theoretic Characterization of Tight Language Models,” in Proceedings of the Association for Computational Linguistics (ACL), 2023, p. 9744–9770.
[BibTeX] [Link]

@InProceedings{du-et-al-2023,
author = "Li Du and Lucas Torroba Hennigen and Tiago Pimentel
and Clara Meister and Jason Eisner and Ryan Cotterell",
title = "A Measure-Theoretic Characterization of Tight Language
Models",
booktitle = "Proceedings of the Association for Computational
Linguistics (ACL)",
year = "2023",
month = jul,
pages = "9744--9770",
URL = "http://cs.jhu.edu/~jason/papers/#du-et-al-2023",
}

A. Opedal, R. Zmigrod, T. Vieira, Ryan Cotterell, and J. Eisner, “Efficient Semiring-Weighted Earley Parsing,” in Proceedings of the Association for Computational Linguistics (ACL), 2023, p. 3687–3713.
[BibTeX] [Link]

@InProceedings{opedal-et-al-2023,
author = "Andreas Opedal and Ran Zmigrod and Tim Vieira and Ryan
Cotterell and Jason Eisner",
title = "Efficient Semiring-Weighted {E}arley Parsing",
booktitle = "Proceedings of the Association for Computational
Linguistics (ACL)",
year = "2023",
month = jul,
pages = "3687--3713",
URL = "http://cs.jhu.edu/~jason/papers/#opedal-et-al-2023",
}

Yuxiang Guo, Cheng-Fang Peng, R. Prabhakar, Chun Pong Lau, and R. Chellappa, “GADER: GAit DEtection and Recognition in the Wild,” in arXiv.org, 2023.
[BibTeX] [Link]

@inproceedings{260202959,
title = {GADER: GAit DEtection and Recognition in the Wild},
author = {{Yuxiang Guo} and {Cheng-Fang Peng} and {R. Prabhakar} and {Chun Pong Lau} and {R. Chellappa}},
year = 2023,
month = {7},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/883f84e5fd894cec4b0364999a0461534f048cee},
}

Thanh Nguyen-Tang and R. Arora, “Provably Efficient Neural Offline Reinforcement Learning via Perturbed Rewards,” in arXiv.org, 2023.
[BibTeX] [Link]

@inproceedings{257206027,
title = {Provably Efficient Neural Offline Reinforcement Learning via Perturbed Rewards},
author = {{Thanh Nguyen-Tang} and {R. Arora}},
year = 2023,
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/a8dac0d0837ac4800f4462a121c59a98a05531ee},
}

J. Villalba, Jonas Borgstrom, Maliha Jahan, Saurabh Kataria, Leibny Paola Garcia, P. Torres-Carrasquillo, and N. Dehak, “Advances in Language Recognition in Low Resource African Languages: The JHU-MIT Submission for NIST LRE22,” in Interspeech, 2023.
[BibTeX] [Link]

@inproceedings{260918551,
title = {Advances in Language Recognition in Low Resource African Languages: The JHU-MIT Submission for NIST LRE22},
author = {{J. Villalba} and {Jonas Borgstrom} and {Maliha Jahan} and {Saurabh Kataria} and {Leibny Paola Garcia} and {P. Torres-Carrasquillo} and {N. Dehak}},
year = 2023,
month = {8},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/51aca07d500c44ebde896b8df3b0388dd3ade489},
}

Pengfei Yu, Heng Ji, Shih-Fu Chang, and Kevin Duh, “MULTIMEDIA CURRICULUM LEARNING FOR LANGUAGE ACQUISITION.” 2023.
[BibTeX] [Link]

@inproceedings{259923580,
title = {MULTIMEDIA CURRICULUM LEARNING FOR LANGUAGE ACQUISITION},
author = {{Pengfei Yu} and {Heng Ji} and {Shih-Fu Chang} and {Kevin Duh}},
year = 2023,
booktitle = {},
url = {https://www.semanticscholar.org/paper/7c7d8f106f8cd1bdadfd3b46f6ebb1509cb1be42},
}

E. Schumacher, J. Mayfield, and M. Dredze, “On the Surprising Effectiveness of Name Matching Alone in Autoregressive Entity Linking,” in Proceedings of the First Workshop on Matching From Unstructured and Structured Data (MATCHING 2023), Toronto, ON, Canada, 2023, p. 58–69. doi:10.18653/v1/2023.matching-1.6
[BibTeX] [Abstract] [Link]

Fifteen years of work on entity linking has established the importance of different information sources in making linking decisions: mention and entity name similarity, contextual relevance, and features of the knowledge base. Modern state-of-the-art systems build on these features, including through neural representations (Wu et al., 2020). In contrast to this trend, the autoregressive language model GENRE (De Cao et al., 2021) generates normalized entity names for mentions and beats many other entity linking systems, despite making no use of knowledge base (KB) information. How is this possible? We analyze the behavior of GENRE on several entity linking datasets and demonstrate that its performance stems from memorization of name patterns. In contrast, it fails in cases that might benefit from using the KB. We experiment with a modification to the model to enable it to utilize KB information, highlighting challenges to incorporating traditional entity linking information sources into autoregressive models.

@inproceedings{schumacher-etal-2023-surprising,
title = "On the Surprising Effectiveness of Name Matching Alone in Autoregressive Entity Linking",
author = "Schumacher, Elliot and
Mayfield, James and
Dredze, Mark",
editor = "Hruschka, Estevam and
Mitchell, Tom and
Rahman, Sajjadur and
Mladeni{\'c}, Dunja and
Grobelnik, Marko",
booktitle = "Proceedings of the First Workshop on Matching From Unstructured and Structured Data (MATCHING 2023)",
month = jul,
year = "2023",
address = "Toronto, ON, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.matching-1.6",
doi = "10.18653/v1/2023.matching-1.6",
pages = "58--69",
abstract = "Fifteen years of work on entity linking has established the importance of different information sources in making linking decisions: mention and entity name similarity, contextual relevance, and features of the knowledge base. Modern state-of-the-art systems build on these features, including through neural representations (Wu et al., 2020). In contrast to this trend, the autoregressive language model GENRE (De Cao et al., 2021) generates normalized entity names for mentions and beats many other entity linking systems, despite making no use of knowledge base (KB) information. How is this possible? We analyze the behavior of GENRE on several entity linking datasets and demonstrate that its performance stems from memorization of name patterns. In contrast, it fails in cases that might benefit from using the KB. We experiment with a modification to the model to enable it to utilize KB information, highlighting challenges to incorporating traditional entity linking information sources into autoregressive models.",
}

Enayat Ullah and R. Arora, “Generalization bounds for Kernel Canonical Correlation Analysis,” in Trans. Mach. Learn. Res., 2023.
[BibTeX] [Link]

@inproceedings{258766137,
title = {Generalization bounds for Kernel Canonical Correlation Analysis},
author = {{Enayat Ullah} and {R. Arora}},
year = 2023,
booktitle = {Trans. Mach. Learn. Res.},
url = {https://www.semanticscholar.org/paper/4a55079d0145870461cbe2a48f53e40e64b7db3d},
}

Thanh Nguyen-Tang and R. Arora, “VIPeR: Provably Efficient Algorithm for Offline RL with Neural Function Approximation,” in International Conference on Learning Representations, 2023.
[BibTeX] [Link]

@inproceedings{257366012,
title = {VIPeR: Provably Efficient Algorithm for Offline RL with Neural Function Approximation},
author = {{Thanh Nguyen-Tang} and {R. Arora}},
year = 2023,
month = {2},
booktitle = {International Conference on Learning Representations},
url = {https://www.semanticscholar.org/paper/7d200b868cb92657a68ac64c112a2cd0a4045f87},
}

D. Li, A. Butala, T. Meyer, E. Oh, C. Motley, L. Moro-Velázquez, and N. Dehak, “Automating analysis of eye movement and feature extraction for different neurodegenerative disorders,” in medRxiv, 2023.
[BibTeX] [Link]

@inproceedings{258997975,
title = {Automating analysis of eye movement and feature extraction for different neurodegenerative disorders},
author = {{D. Li} and {A. Butala} and {T. Meyer} and {E. Oh} and {C. Motley} and {L. Moro-Velázquez} and {N. Dehak}},
year = 2023,
month = {6},
booktitle = {medRxiv},
url = {https://www.semanticscholar.org/paper/2b5f1cfc2b507561bd463b0a5ac14fd92d75dc50},
}

Cihan Xiao, Henry Li Xinyuan, Jinyi Yang, Dongji Gao, Matthew Wiesner, Kevin Duh, and S. Khudanpur, “HK-LegiCoST: Leveraging Non-Verbatim Transcripts for Speech Translation,” in Interspeech, 2023.
[BibTeX] [Link]

@inproceedings{259203410,
title = {HK-LegiCoST: Leveraging Non-Verbatim Transcripts for Speech Translation},
author = {{Cihan Xiao} and {Henry Li Xinyuan} and {Jinyi Yang} and {Dongji Gao} and {Matthew Wiesner} and {Kevin Duh} and {S. Khudanpur}},
year = 2023,
month = {6},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/74173dec94055d7f4051aa2e80be31ccd2bde596},
}

A. Favaro, Yi-Ting Tsai, A. Butala, Thomas Thebaud, J. Villalba, N. Dehak, and L. Moro-Velázquez, “Interpretable Speech Features vs. DNN Embeddings: What to Use in the Automatic Assessment of Parkinson’s Disease in Multi-lingual Scenarios,” in medRxiv, 2023.
[BibTeX] [Link]

@inproceedings{259047417,
title = {Interpretable Speech Features vs. DNN Embeddings: What to Use in the Automatic Assessment of Parkinson's Disease in Multi-lingual Scenarios},
author = {{A. Favaro} and {Yi-Ting Tsai} and {A. Butala} and {Thomas Thebaud} and {J. Villalba} and {N. Dehak} and {L. Moro-Velázquez}},
year = 2023,
month = {6},
booktitle = {medRxiv},
url = {https://www.semanticscholar.org/paper/8d18efe22ad66b53a0a13fc71c9b57c41b7790d0},
}

Saurabh Kataria, J. Villalba, Laureano Moro-Vel’azquez, Thomas Thebaud, and N. Dehak, “Self-FiLM: Conditioning GANs with self-supervised representations for bandwidth extension based speaker recognition,” in Interspeech, 2023.
[BibTeX] [Link]

@inproceedings{257378503,
title = {Self-FiLM: Conditioning GANs with self-supervised representations for bandwidth extension based speaker recognition},
author = {{Saurabh Kataria} and {J. Villalba} and {Laureano Moro-Vel'azquez} and {Thomas Thebaud} and {N. Dehak}},
year = 2023,
month = {3},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/03e266795339008e9366daabfd2a2db2fbd51151},
}

P. Abadir, Ramalingam Chellappa, N. Choudhry, G. Demiris, Deepak Ganesan, Jason Karlawish, Rose M Li, Jason H. Moore, J. Walston, Benjamin Najim Alicia I. Mathias Thomas K. M. Suchi Esther Marlin Dehak Arbaje Unberath Cudjoe Saria Oh Lunde, Benjamin M Marlin, N. Dehak, A. Arbaje, M. Unberath, T. Cudjoe, S. Saria, Esther Oh, N. Lundebjerg, C. Chute, Phillip Phan, Quincy M. Samus, and Nancy L. Schoenborn, “The promise of AI and technology to improve quality of life and care for older adults,” in Nature Aging, 2023.
[BibTeX] [Link]

@inproceedings{258909084,
title = {The promise of AI and technology to improve quality of life and care for older adults},
author = {{P. Abadir} and {Ramalingam Chellappa} and {N. Choudhry} and {G. Demiris} and {Deepak Ganesan} and {Jason Karlawish} and {Rose M Li} and {Jason H. Moore} and {J. Walston} and {Benjamin Najim Alicia I. Mathias Thomas K. M. Suchi Esther Marlin Dehak Arbaje Unberath Cudjoe Saria Oh Lunde} and {Benjamin M Marlin} and {N. Dehak} and {A. Arbaje} and {M. Unberath} and {T. Cudjoe} and {S. Saria} and {Esther Oh} and {N. Lundebjerg} and {C. Chute} and {Phillip Phan} and {Quincy M. Samus} and {Nancy L. Schoenborn}},
year = 2023,
month = {5},
booktitle = {Nature Aging},
url = {https://www.semanticscholar.org/paper/24eafaf005bd6d73870b66525e8978b760e7b3ad},
}

A. Favaro, Tianyu Cao, Thomas Thebaud, J. Villalba, A. Butala, N. Dehak, and L. Moro-Velázquez, “Do Phonatory Features Display Robustness to Characterize Parkinsonian Speech Across Corpora?,” in Interspeech, 2023.
[BibTeX] [Link]

@inproceedings{260914548,
title = {Do Phonatory Features Display Robustness to Characterize Parkinsonian Speech Across Corpora?},
author = {{A. Favaro} and {Tianyu Cao} and {Thomas Thebaud} and {J. Villalba} and {A. Butala} and {N. Dehak} and {L. Moro-Velázquez}},
year = 2023,
month = {8},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/562d06b0cddb553a76e6b68f6f2ba470a17bb5d4},
}

K. Duh and X. Zhang, “AutoML for NLP,” in Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: Tutorial Abstracts, Dubrovnik, Croatia, 2023, p. 25–26. doi:10.18653/v1/2023.eacl-tutorials.5
[BibTeX] [Abstract] [Link]

Automated Machine Learning (AutoML) is an emerging field that has potential to impact how we build models in NLP. As an umbrella term that includes topics like hyperparameter optimization and neural architecture search, AutoML has recently become mainstream at major conferences such as NeurIPS, ICML, and ICLR. What does this mean to NLP? Currently, models are often built in an ad hoc process: we might borrow default hyperparameters from previous work and try a few variant architectures, but it is never guaranteed that final trained model is optimal. Automation can introduce rigor in this model-building process. This tutorial will summarize the main AutoML techniques and illustrate how to apply them to improve the NLP model-building process.

@inproceedings{duh-zhang-2023-automl,
title = "{A}uto{ML} for {NLP}",
author = "Duh, Kevin and
Zhang, Xuan",
editor = "Zanzotto, Fabio Massimo and
Pradhan, Sameer",
booktitle = "Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: Tutorial Abstracts",
month = may,
year = "2023",
address = "Dubrovnik, Croatia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.eacl-tutorials.5",
doi = "10.18653/v1/2023.eacl-tutorials.5",
pages = "25--26",
abstract = "Automated Machine Learning (AutoML) is an emerging field that has potential to impact how we build models in NLP. As an umbrella term that includes topics like hyperparameter optimization and neural architecture search, AutoML has recently become mainstream at major conferences such as NeurIPS, ICML, and ICLR. What does this mean to NLP? Currently, models are often built in an ad hoc process: we might borrow default hyperparameters from previous work and try a few variant architectures, but it is never guaranteed that final trained model is optimal. Automation can introduce rigor in this model-building process. This tutorial will summarize the main AutoML techniques and illustrate how to apply them to improve the NLP model-building process.",
}

Kapil D. Katyal, R. Chellappa, Ketul Shah, Arun V. Reddy, Judy Hoffman, William Paul, Rohita Mocharla, D. Handelman, and Celso de Melo, “Leveraging synthetic data for robust gesture recognition,” in Defense + Commercial Sensing, 2023.
[BibTeX] [Link]

@inproceedings{258383693,
title = {Leveraging synthetic data for robust gesture recognition},
author = {{Kapil D. Katyal} and {R. Chellappa} and {Ketul Shah} and {Arun V. Reddy} and {Judy Hoffman} and {William Paul} and {Rohita Mocharla} and {D. Handelman} and {Celso de Melo}},
year = 2023,
month = {6},
booktitle = {Defense + Commercial Sensing},
url = {https://www.semanticscholar.org/paper/922198774621861436721bd923dc0f0028872a84},
}

Paul McNamee and Kevin Duh, “An Extensive Exploration of Back-Translation in 60 Languages,” in Annual Meeting of the Association for Computational Linguistics, 2023.
[BibTeX] [Link]

@inproceedings{259859140,
title = {An Extensive Exploration of Back-Translation in 60 Languages},
author = {{Paul McNamee} and {Kevin Duh}},
year = 2023,
booktitle = {Annual Meeting of the Association for Computational Linguistics},
url = {https://www.semanticscholar.org/paper/3b1cea929fb0a44886ed654c9ca88a9df959f371},
}

Shijie Wu, Ozan Irsoy, Steven Lu, Vadim Dabravolski, Mark Dredze, Sebastian Gehrmann, P. Kambadur, D. Rosenberg, and Gideon Mann, “BloombergGPT: A Large Language Model for Finance,” in arXiv.org, 2023.
[BibTeX] [Link]

@inproceedings{257833842,
title = {BloombergGPT: A Large Language Model for Finance},
author = {{Shijie Wu} and {Ozan Irsoy} and {Steven Lu} and {Vadim Dabravolski} and {Mark Dredze} and {Sebastian Gehrmann} and {P. Kambadur} and {D. Rosenberg} and {Gideon Mann}},
year = 2023,
month = {3},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/83edcfbb206ddad38a971d605da09390604248ea},
}

T. Meyer, A. Favaro, Tianyu Cao, A. Butala, E. Oh, C. Motley, P. Irazoqui, N. Dehak, and L. Moro-Velázquez, “Deep Stroop: Using eye tracking and speech processing to characterize people with neurodegenerative disorders while performing the Stroop Test,” in medRxiv, 2023.
[BibTeX] [Link]

@inproceedings{258997982,
title = {Deep Stroop: Using eye tracking and speech processing to characterize people with neurodegenerative disorders while performing the Stroop Test},
author = {{T. Meyer} and {A. Favaro} and {Tianyu Cao} and {A. Butala} and {E. Oh} and {C. Motley} and {P. Irazoqui} and {N. Dehak} and {L. Moro-Velázquez}},
year = 2023,
month = {6},
booktitle = {medRxiv},
url = {https://www.semanticscholar.org/paper/172e04d89d89109626cba6a5b2d4d8a736bd145d},
}

Jonah P. Sengupta, M. A. Tomlinson, Daniel R. Mendat, M. Villemur, and A. Andreou, “Asynchronous, Spatiotemporal Filtering using an Analog Cellular Neural Network Processor,” in International Symposium on Circuits and Systems, 2023.
[BibTeX] [Link]

@inproceedings{260003954,
title = {Asynchronous, Spatiotemporal Filtering using an Analog Cellular Neural Network Processor},
author = {{Jonah P. Sengupta} and {M. A. Tomlinson} and {Daniel R. Mendat} and {M. Villemur} and {A. Andreou}},
year = 2023,
month = {5},
booktitle = {International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/30446a1b3ca0fc61c3b672d5a284e0dcb761fe6d},
}

Saurabhchand Bhati, J. Villalba, L. Moro-Velázquez, Thomas Thebaud, and N. Dehak, “Segmental SpeechCLIP: Utilizing Pretrained Image-text Models for Audio-Visual Learning,” in Interspeech, 2023.
[BibTeX] [Link]

@inproceedings{260909100,
title = {Segmental SpeechCLIP: Utilizing Pretrained Image-text Models for Audio-Visual Learning},
author = {{Saurabhchand Bhati} and {J. Villalba} and {L. Moro-Velázquez} and {Thomas Thebaud} and {N. Dehak}},
year = 2023,
month = {8},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/1617d389b7947161f2943e2d30afeb1856052b14},
}

Saurabhchand Bhati, J. Villalba, L. Moro-Velázquez, Thomas Thebaud, and N. Dehak, “Leveraging Pretrained Image-text Models for Improving Audio-Visual Learning,” in arXiv.org, 2023.
[BibTeX] [Link]

@inproceedings{261682358,
title = {Leveraging Pretrained Image-text Models for Improving Audio-Visual Learning},
author = {{Saurabhchand Bhati} and {J. Villalba} and {L. Moro-Velázquez} and {Thomas Thebaud} and {N. Dehak}},
year = 2023,
month = {9},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/ada7b279876196a283a8379729212338386c7eba},
}

R. Chellappa, “The unsung hero: how synthetic data has helped computer vision, machine learning, and AI,” in Synthetic Data for Artificial Intelligence and Machine Learning: Tools, Techniques, and Applications, 2023.
[BibTeX] [Link]

@inproceedings{259436318,
title = {The unsung hero: how synthetic data has helped computer vision, machine learning, and AI},
author = {{R. Chellappa}},
year = 2023,
month = {6},
booktitle = {Synthetic Data for Artificial Intelligence and Machine Learning: Tools, Techniques, and Applications},
url = {https://www.semanticscholar.org/paper/c061dd875146aa8d87b5bfe45eea73df8da3c373},
}

Enayat Ullah, Harry Lang, R. Arora, and V. Braverman, “Clustering using Approximate Nearest Neighbour Oracles,” in Trans. Mach. Learn. Res., 2023.
[BibTeX] [Link]

@inproceedings{258766141,
title = {Clustering using Approximate Nearest Neighbour Oracles},
author = {{Enayat Ullah} and {Harry Lang} and {R. Arora} and {V. Braverman}},
year = 2023,
booktitle = {Trans. Mach. Learn. Res.},
url = {https://www.semanticscholar.org/paper/2e864475d80f551d97232f9a6cba079dd128c54d},
}

Jeremy Gwinnup and Kevin Duh, “A Survey of Vision-Language Pre-training from the Lens of Multimodal Machine Translation,” in arXiv.org, 2023.
[BibTeX] [Link]

@inproceedings{259137602,
title = {A Survey of Vision-Language Pre-training from the Lens of Multimodal Machine Translation},
author = {{Jeremy Gwinnup} and {Kevin Duh}},
year = 2023,
month = {6},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/c581d2ad3b092a2cc152d0c6f55fd6320f78eb3a},
}

Manoj Jain, Salil Bhargava, R. Arora, R. Joshi, Ravinder Kumar, Deepak Saxena, Kiran Rade, and Rebecca Martin, “Using a Quality Improvement Tool, Plan-Do-Study-Act Cycle, to Boost TB Notification in India post-Covid-19 Pandemic,” in Indian Journal of Tuberculosis, 2023.
[BibTeX] [Link]

@inproceedings{262185166,
title = {Using a Quality Improvement Tool, Plan-Do-Study-Act Cycle, to Boost TB Notification in India post-Covid-19 Pandemic},
author = {{Manoj Jain} and {Salil Bhargava} and {R. Arora} and {R. Joshi} and {Ravinder Kumar} and {Deepak Saxena} and {Kiran Rade} and {Rebecca Martin}},
year = 2023,
month = {9},
booktitle = {Indian Journal of Tuberculosis},
url = {https://www.semanticscholar.org/paper/acbaffb72d4c3bd7c9a12d6c756a4a207dea3703},
}

Sai Saketh Rambhatla, Ishan Misra, R. Chellappa, and Abhinav Shrivastava, “MOST: Multiple Object localization with Self-supervised Transformers for object discovery,” in IEEE International Conference on Computer Vision, 2023.
[BibTeX] [Link]

@inproceedings{258060050,
title = {MOST: Multiple Object localization with Self-supervised Transformers for object discovery},
author = {{Sai Saketh Rambhatla} and {Ishan Misra} and {R. Chellappa} and {Abhinav Shrivastava}},
year = 2023,
month = {4},
booktitle = {IEEE International Conference on Computer Vision},
url = {https://www.semanticscholar.org/paper/3be837073f08eecc01e1bc742c541c5f0e644946},
}

Tianyu Cao, L. Moro-Velázquez, Piotr Żelasko, J. Villalba, and N. Dehak, “Vsameter: Evaluation of a New Open-Source Tool to Measure Vowel Space Area and Related Metrics,” in Spoken Language Technology Workshop, 2023.
[BibTeX] [Link]

@inproceedings{256356339,
title = {Vsameter: Evaluation of a New Open-Source Tool to Measure Vowel Space Area and Related Metrics},
author = {{Tianyu Cao} and {L. Moro-Velázquez} and {Piotr Żelasko} and {J. Villalba} and {N. Dehak}},
year = 2023,
month = {1},
booktitle = {Spoken Language Technology Workshop},
url = {https://www.semanticscholar.org/paper/dd3d00bf410d95d15569443387082da13a2462c4},
}

Martin Sustek, Samik Sadhu, L. Burget, H. Hermansky, J. Villalba, L. Moro-Velázquez, and N. Dehak, “Stabilized training of joint energy-based models and their practical applications,” in arXiv.org, 2023.
[BibTeX] [Link]

@inproceedings{257404851,
title = {Stabilized training of joint energy-based models and their practical applications},
author = {{Martin Sustek} and {Samik Sadhu} and {L. Burget} and {H. Hermansky} and {J. Villalba} and {L. Moro-Velázquez} and {N. Dehak}},
year = 2023,
month = {3},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/46fd16213979b00e741b926539ad4ba7a1acd1cf},
}

Daniel R. Mendat, Jonah P. Sengupta, Gaspar Tognetti, M. Villemur, P. Pouliquen, Sergio Montano, Kayode A. Sanni, J. Molin, Nishant Zachariah, I. Doxas, and A. Andreou, “A RISC-V Neuromorphic Micro-Controller Unit (vMCU) with Event-Based Physical Interface and Computational Memory for Low-Latency Machine Perception and Intelligence at the Edge,” in International Symposium on Circuits and Systems, 2023.
[BibTeX] [Link]

@inproceedings{260003158,
title = {A RISC-V Neuromorphic Micro-Controller Unit (vMCU) with Event-Based Physical Interface and Computational Memory for Low-Latency Machine Perception and Intelligence at the Edge},
author = {{Daniel R. Mendat} and {Jonah P. Sengupta} and {Gaspar Tognetti} and {M. Villemur} and {P. Pouliquen} and {Sergio Montano} and {Kayode A. Sanni} and {J. Molin} and {Nishant Zachariah} and {I. Doxas} and {A. Andreou}},
year = 2023,
month = {5},
booktitle = {International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/0d2f0f6eb40d3be7b97a19315439721cf7ae8469},
}

A. Favaro, L. Moro-Velázquez, A. Butala, C. Motley, Tianyu Cao, R. Stevens, J. Villalba, and N. Dehak, “Multilingual evaluation of interpretable biomarkers to represent language and speech patterns in Parkinson’s disease,” in Frontiers in Neurology, 2023.
[BibTeX] [Link]

@inproceedings{257323163,
title = {Multilingual evaluation of interpretable biomarkers to represent language and speech patterns in Parkinson's disease},
author = {{A. Favaro} and {L. Moro-Velázquez} and {A. Butala} and {C. Motley} and {Tianyu Cao} and {R. Stevens} and {J. Villalba} and {N. Dehak}},
year = 2023,
month = {3},
booktitle = {Frontiers in Neurology},
url = {https://www.semanticscholar.org/paper/3ed2d557a323c9fc39dbdd64e0ffab064b35a7f9},
}

Jonah P. Sengupta and A. Andreou, “Retinomorphic Channel Design and Considerations,” in Annual Conference on Information Sciences and Systems, 2023.
[BibTeX] [Link]

@inproceedings{258074434,
title = {Retinomorphic Channel Design and Considerations},
author = {{Jonah P. Sengupta} and {A. Andreou}},
year = 2023,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/7f97effeed913a6089ca98d576d585401e251f9b},
}

A. DeLucia, M. Dredze, and A. L. Buczak, “A Multi-instance Learning Approach to Civil Unrest Event Detection on Twitter,” in Proceedings of the 6th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text, Varna, Bulgaria, 2023, p. 18–33.
[BibTeX] [Abstract] [Link]

Social media has become an established platform for people to organize and take offline actions, often in the form of civil unrest. Understanding these events can help support pro-democratic movements. The primary method to detect these events on Twitter relies on aggregating many tweets, but this includes many that are not relevant to the task. We propose a multi-instance learning (MIL) approach, which jointly identifies relevant tweets and detects civil unrest events. We demonstrate that MIL improves civil unrest detection over methods based on simple aggregation. Our best model achieves a 0.73 F1 on the Global Civil Unrest on Twitter (G-CUT) dataset.

@inproceedings{delucia-etal-2023-multi,
title = "A Multi-instance Learning Approach to Civil Unrest Event Detection on {T}witter",
author = "DeLucia, Alexandra and
Dredze, Mark and
Buczak, Anna L.",
editor = {H{\"u}rriyeto{\u{g}}lu, Ali and
Tanev, Hristo and
Zavarella, Vanni and
Yeniterzi, Reyyan and
Y{\"o}r{\"u}k, Erdem and
Slavcheva, Milena},
booktitle = "Proceedings of the 6th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text",
month = sep,
year = "2023",
address = "Varna, Bulgaria",
publisher = "INCOMA Ltd., Shoumen, Bulgaria",
url = "https://aclanthology.org/2023.case-1.3",
pages = "18--33",
abstract = "Social media has become an established platform for people to organize and take offline actions, often in the form of civil unrest. Understanding these events can help support pro-democratic movements. The primary method to detect these events on Twitter relies on aggregating many tweets, but this includes many that are not relevant to the task. We propose a multi-instance learning (MIL) approach, which jointly identifies relevant tweets and detects civil unrest events. We demonstrate that MIL improves civil unrest detection over methods based on simple aggregation. Our best model achieves a 0.73 F1 on the Global Civil Unrest on Twitter (G-CUT) dataset.",
}

Enayat Ullah and R. Arora, “From Adaptive Query Release to Machine Unlearning,” in International Conference on Machine Learning, 2023.
[BibTeX] [Link]

@inproceedings{260091661,
title = {From Adaptive Query Release to Machine Unlearning},
author = {{Enayat Ullah} and {R. Arora}},
year = 2023,
month = {7},
booktitle = {International Conference on Machine Learning},
url = {https://www.semanticscholar.org/paper/ea3eff68041f3a22b984578e8da8533aa3f766de},
}

A. Favaro, C. Motley, Tianyu Cao, Miguel Iglesias, A. Butala, E. Oh, R. Stevens, J. Villalba, N. Dehak, and L. Moro-Velázquez, “A Multi-Modal Array of Interpretable Features to Evaluate Language and Speech Patterns in Different Neurological Disorders,” in Spoken Language Technology Workshop, 2023.
[BibTeX] [Link]

@inproceedings{256353599,
title = {A Multi-Modal Array of Interpretable Features to Evaluate Language and Speech Patterns in Different Neurological Disorders},
author = {{A. Favaro} and {C. Motley} and {Tianyu Cao} and {Miguel Iglesias} and {A. Butala} and {E. Oh} and {R. Stevens} and {J. Villalba} and {N. Dehak} and {L. Moro-Velázquez}},
year = 2023,
month = {1},
booktitle = {Spoken Language Technology Workshop},
url = {https://www.semanticscholar.org/paper/40eb935374d67b7b9979e0c9333c291d188c472b},
}

Helin Wang, Thomas Thebaud, J. Villalba, Myra Sydnor, Becky Lammers, N. Dehak, and L. Moro-Velázquez, “DuTa-VC: A Duration-aware Typical-to-atypical Voice Conversion Approach with Diffusion Probabilistic Model,” in Interspeech, 2023.
[BibTeX] [Link]

@inproceedings{259202766,
title = {DuTa-VC: A Duration-aware Typical-to-atypical Voice Conversion Approach with Diffusion Probabilistic Model},
author = {{Helin Wang} and {Thomas Thebaud} and {J. Villalba} and {Myra Sydnor} and {Becky Lammers} and {N. Dehak} and {L. Moro-Velázquez}},
year = 2023,
month = {6},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/bf6339e920466f2dc7dc0da5edde5b3187cf9d0d},
}

Saurabhchand Bhati, J. Villalba, Piotr Żelasko, L. Moro-Velázquez, and N. Dehak, “Regularizing Contrastive Predictive Coding for Speech Applications.” 2023.
[BibTeX] [Link]

@inproceedings{258079344,
title = {Regularizing Contrastive Predictive Coding for Speech Applications},
author = {{Saurabhchand Bhati} and {J. Villalba} and {Piotr Żelasko} and {L. Moro-Velázquez} and {N. Dehak}},
year = 2023,
month = {4},
booktitle = {},
url = {https://www.semanticscholar.org/paper/47ac48e7ee37e7cf4d3bb183477e42d6c5632b64},
}

Neha Verma, Kenton Murray, and Kevin Duh, “Exploring Representational Disparities Between Multilingual and Bilingual Translation Models,” in arXiv.org, 2023.
[BibTeX] [Link]

@inproceedings{258841100,
title = {Exploring Representational Disparities Between Multilingual and Bilingual Translation Models},
author = {{Neha Verma} and {Kenton Murray} and {Kevin Duh}},
year = 2023,
month = {5},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/6321d7eec951dd1c6cea44a45f425b774d1b6b26},
}

David Mueller, Nicholas Andrews, and Mark Dredze, “Do Text-to-Text Multi-Task Learners Suffer from Task Conflict?,” in Conference on Empirical Methods in Natural Language Processing, 2022.
[BibTeX] [Link]

@inproceedings{254591386,
title = {Do Text-to-Text Multi-Task Learners Suffer from Task Conflict?},
author = {{David Mueller} and {Nicholas Andrews} and {Mark Dredze}},
year = 2022,
month = {12},
booktitle = {Conference on Empirical Methods in Natural Language Processing},
url = {https://www.semanticscholar.org/paper/2843661ee0d5fa159165beba50c345566cc44c57},
}

C. Chen, L. Moro-Velázquez, A. Ožbolt, A. Butala, A. Pantelyat, and N. Dehak, “Phonatory Analysis on Parkinson’s Disease Patients Attending Singing and Discussion Therapy (Parkinsonics) using Signal Processing Techniques,” in IEEE Signal Processing in Medicine and Biology Symposium, 2022.
[BibTeX] [Link]

@inproceedings{256034037,
title = {Phonatory Analysis on Parkinson's Disease Patients Attending Singing and Discussion Therapy (Parkinsonics) using Signal Processing Techniques},
author = {{C. Chen} and {L. Moro-Velázquez} and {A. Ožbolt} and {A. Butala} and {A. Pantelyat} and {N. Dehak}},
year = 2022,
month = {12},
booktitle = {IEEE Signal Processing in Medicine and Biology Symposium},
url = {https://www.semanticscholar.org/paper/513937e2300445136193356fb6fdae3753d09770},
}

K. Marchisio, N. Verma, K. Duh, and P. Koehn, “IsoVec: Controlling the Relative Isomorphism of Word Embedding Spaces,” in Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, Abu Dhabi, United Arab Emirates, 2022, p. 6019–6033. doi:10.18653/v1/2022.emnlp-main.404
[BibTeX] [Abstract] [Link]

The ability to extract high-quality translation dictionaries from monolingual word embedding spaces depends critically on the geometric similarity of the spaces{–-}their degree of {“}isomorphism.{”} We address the root-cause of faulty cross-lingual mapping: that word embedding training resulted in the underlying spaces being non-isomorphic. We incorporate global measures of isomorphism directly into the skipgram loss function, successfully increasing the relative isomorphism of trained word embedding spaces and improving their ability to be mapped to a shared cross-lingual space. The result is improved bilingual lexicon induction in general data conditions, under domain mismatch, and with training algorithm dissimilarities. We release IsoVec at \url{https://github.com/kellymarchisio/isovec}.

@inproceedings{marchisio-etal-2022-isovec,
title = "{I}so{V}ec: Controlling the Relative Isomorphism of Word Embedding Spaces",
author = "Marchisio, Kelly and
Verma, Neha and
Duh, Kevin and
Koehn, Philipp",
editor = "Goldberg, Yoav and
Kozareva, Zornitsa and
Zhang, Yue",
booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.emnlp-main.404",
doi = "10.18653/v1/2022.emnlp-main.404",
pages = "6019--6033",
abstract = "The ability to extract high-quality translation dictionaries from monolingual word embedding spaces depends critically on the geometric similarity of the spaces{---}their degree of {``}isomorphism.{''} We address the root-cause of faulty cross-lingual mapping: that word embedding training resulted in the underlying spaces being non-isomorphic. We incorporate global measures of isomorphism directly into the skipgram loss function, successfully increasing the relative isomorphism of trained word embedding spaces and improving their ability to be mapped to a shared cross-lingual space. The result is improved bilingual lexicon induction in general data conditions, under domain mismatch, and with training algorithm dissimilarities. We release IsoVec at \url{https://github.com/kellymarchisio/isovec}.",
}

Trevor Meyer, L. Moro-Velázquez, Seneca Motley, A. Butala, Ashley M Paul, Quincy M. Samus, Pedro P. Irazoqui, N. Dehak, and Esther S. Oh, “Automatic Extraction of Oculographic Signals as Digital Biomarkers for Alzheimer’s Disease,” in Alzheimer’s & Dementia, 2022.
[BibTeX] [Link]

@inproceedings{254879636,
title = {Automatic Extraction of Oculographic Signals as Digital Biomarkers for Alzheimer's Disease},
author = {{Trevor Meyer} and {L. Moro-Velázquez} and {Seneca Motley} and {A. Butala} and {Ashley M Paul} and {Quincy M. Samus} and {Pedro P. Irazoqui} and {N. Dehak} and {Esther S. Oh}},
year = 2022,
month = {12},
booktitle = {Alzheimer's & Dementia},
url = {https://www.semanticscholar.org/paper/e5a0988cdd73b981611be9fe06e0b7328ff1c0d0},
}

D. D. Kairamkonda, P. S. Mandaleeka, A. Favaro, C. Motley, A. Butala, E. Oh, R. Stevens, N. Dehak, and L. Moro-Velázquez, “Analysis of Interpretable Handwriting Features to Evaluate Motoric Patterns in Different Neurodegenerative Diseases,” in IEEE Signal Processing in Medicine and Biology Symposium, 2022.
[BibTeX] [Link]

@inproceedings{256034700,
title = {Analysis of Interpretable Handwriting Features to Evaluate Motoric Patterns in Different Neurodegenerative Diseases},
author = {{D. D. Kairamkonda} and {P. S. Mandaleeka} and {A. Favaro} and {C. Motley} and {A. Butala} and {E. Oh} and {R. Stevens} and {N. Dehak} and {L. Moro-Velázquez}},
year = 2022,
month = {12},
booktitle = {IEEE Signal Processing in Medicine and Biology Symposium},
url = {https://www.semanticscholar.org/paper/d10f7b6ab049a92c19e1d9c7792063e85ce60d22},
}

M. Keymanesh, A. Benton, and M. Dredze, “What Makes Data-to-Text Generation Hard for Pretrained Language Models?,” in Proceedings of the 2nd Workshop on Natural Language Generation, Evaluation, and Metrics (GEM), Abu Dhabi, United Arab Emirates (Hybrid), 2022, p. 539–554. doi:10.18653/v1/2022.gem-1.50
[BibTeX] [Abstract] [Link]

Expressing natural language descriptions of structured facts or relations {–} data-to-text generation (D2T) {–} increases the accessibility of structured knowledge repositories. Previous work shows that pre-trained language models (PLMs) perform remarkably well on this task after fine-tuning on a significant amount of task-specific training data. On the other hand, while auto-regressive PLMs can generalize from a few task examples, their efficacy at D2T is largely unexplored. Furthermore, we have an incomplete understanding of the limits of PLMs on D2T. In this work, we conduct an empirical study of both fine-tuned and auto-regressive PLMs on the DART multi-domain D2T dataset. We consider their performance as a function of the amount of task-specific data and how the data is incorporated into the models: zero and few-shot learning, and fine-tuning of model weights. In addition, we probe the limits of PLMs by measuring performance on subsets of the evaluation data: novel predicates and abstractive test examples. To improve the performance on these subsets, we investigate two techniques: providing predicate descriptions in the context and re-ranking generated candidates by information reflected in the source. Finally, we conduct a human evaluation of model errors and show that D2T generation tasks would benefit from datasets with more careful manual curation.

@inproceedings{keymanesh-etal-2022-makes,
title = "What Makes Data-to-Text Generation Hard for Pretrained Language Models?",
author = "Keymanesh, Moniba and
Benton, Adrian and
Dredze, Mark",
editor = "Bosselut, Antoine and
Chandu, Khyathi and
Dhole, Kaustubh and
Gangal, Varun and
Gehrmann, Sebastian and
Jernite, Yacine and
Novikova, Jekaterina and
Perez-Beltrachini, Laura",
booktitle = "Proceedings of the 2nd Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates (Hybrid)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.gem-1.50",
doi = "10.18653/v1/2022.gem-1.50",
pages = "539--554",
abstract = "Expressing natural language descriptions of structured facts or relations {--} data-to-text generation (D2T) {--} increases the accessibility of structured knowledge repositories. Previous work shows that pre-trained language models (PLMs) perform remarkably well on this task after fine-tuning on a significant amount of task-specific training data. On the other hand, while auto-regressive PLMs can generalize from a few task examples, their efficacy at D2T is largely unexplored. Furthermore, we have an incomplete understanding of the limits of PLMs on D2T. In this work, we conduct an empirical study of both fine-tuned and auto-regressive PLMs on the DART multi-domain D2T dataset. We consider their performance as a function of the amount of task-specific data and how the data is incorporated into the models: zero and few-shot learning, and fine-tuning of model weights. In addition, we probe the limits of PLMs by measuring performance on subsets of the evaluation data: novel predicates and abstractive test examples. To improve the performance on these subsets, we investigate two techniques: providing predicate descriptions in the context and re-ranking generated candidates by information reflected in the source. Finally, we conduct a human evaluation of model errors and show that D2T generation tasks would benefit from datasets with more careful manual curation.",
}

K. Marchisio, A. Saad-Eldin, K. Duh, C. Priebe, and P. Koehn, “Bilingual Lexicon Induction for Low-Resource Languages using Graph Matching via Optimal Transport,” in Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, Abu Dhabi, United Arab Emirates, 2022, p. 2545–2561. doi:10.18653/v1/2022.emnlp-main.164
[BibTeX] [Abstract] [Link]

Bilingual lexicons form a critical component of various natural language processing applications, including unsupervised and semisupervised machine translation and crosslingual information retrieval. In this work, we improve bilingual lexicon induction performance across 40 language pairs with a graph-matching method based on optimal transport. The method is especially strong with low amounts of supervision.

@inproceedings{marchisio-etal-2022-bilingual,
title = "Bilingual Lexicon Induction for Low-Resource Languages using Graph Matching via Optimal Transport",
author = "Marchisio, Kelly and
Saad-Eldin, Ali and
Duh, Kevin and
Priebe, Carey and
Koehn, Philipp",
editor = "Goldberg, Yoav and
Kozareva, Zornitsa and
Zhang, Yue",
booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.emnlp-main.164",
doi = "10.18653/v1/2022.emnlp-main.164",
pages = "2545--2561",
abstract = "Bilingual lexicons form a critical component of various natural language processing applications, including unsupervised and semisupervised machine translation and crosslingual information retrieval. In this work, we improve bilingual lexicon induction performance across 40 language pairs with a graph-matching method based on optimal transport. The method is especially strong with low amounts of supervision.",
}

E. Schumacher, J. Mayfield, and M. Dredze, “Zero-shot Cross-Language Transfer of Monolingual Entity Linking Models,” in Proceedings of the 2nd Workshop on Multi-lingual Representation Learning (MRL), Abu Dhabi, United Arab Emirates (Hybrid), 2022, p. 38–51. doi:10.18653/v1/2022.mrl-1.4
[BibTeX] [Abstract] [Link]

Most entity linking systems, whether mono or multilingual, link mentions to a single English knowledge base. Few have considered linking non-English text to a non-English KB, and therefore, transferring an English entity linking model to both a new document and KB language. We consider the task of zero-shot cross-language transfer of entity linking systems to a new language and KB. We find that a system trained with multilingual representations does reasonably well, and propose improvements to system training that lead to improved recall in most datasets, often matching the in-language performance. We further conduct a detailed evaluation to elucidate the challenges of this setting.

@inproceedings{schumacher-etal-2022-zero,
title = "Zero-shot Cross-Language Transfer of Monolingual Entity Linking Models",
author = "Schumacher, Elliot and
Mayfield, James and
Dredze, Mark",
editor = {Ataman, Duygu and
Gonen, Hila and
Ruder, Sebastian and
Firat, Orhan and
G{\"u}l Sahin, G{\"o}zde and
Mirzakhalov, Jamshidbek},
booktitle = "Proceedings of the 2nd Workshop on Multi-lingual Representation Learning (MRL)",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates (Hybrid)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.mrl-1.4",
doi = "10.18653/v1/2022.mrl-1.4",
pages = "38--51",
abstract = "Most entity linking systems, whether mono or multilingual, link mentions to a single English knowledge base. Few have considered linking non-English text to a non-English KB, and therefore, transferring an English entity linking model to both a new document and KB language. We consider the task of zero-shot cross-language transfer of entity linking systems to a new language and KB. We find that a system trained with multilingual representations does reasonably well, and propose improvements to system training that lead to improved recall in most datasets, often matching the in-language performance. We further conduct a detailed evaluation to elucidate the challenges of this setting.",
}

A. Favaro, Seneca Motley, Quincy M. Samus, A. Butala, N. Dehak, Esther S. Oh, and L. Moro-Velázquez, “Artificial Intelligence Tools to Evaluate Language and Speech Patterns in Alzheimer’s Disease,” in Alzheimer’s & Dementia, 2022.
[BibTeX] [Link]

@inproceedings{254880773,
title = {Artificial Intelligence Tools to Evaluate Language and Speech Patterns in Alzheimer's Disease},
author = {{A. Favaro} and {Seneca Motley} and {Quincy M. Samus} and {A. Butala} and {N. Dehak} and {Esther S. Oh} and {L. Moro-Velázquez}},
year = 2022,
month = {12},
booktitle = {Alzheimer's & Dementia},
url = {https://www.semanticscholar.org/paper/e8f74514d4b195230ddd7dd6b60cabbc7ed240b1},
}

M. Iglesias, A. Favaro, C. Motley, E. Oh, R. Stevens, A. Butala, L. Moro-Velázquez, and N. Dehak, “Cognitive and Acoustic Speech and Language Patterns Occurring in Different Neurodegenerative Disorders while Performing Neuropsychological Tests,” in IEEE Signal Processing in Medicine and Biology Symposium, 2022.
[BibTeX] [Link]

@inproceedings{256033943,
title = {Cognitive and Acoustic Speech and Language Patterns Occurring in Different Neurodegenerative Disorders while Performing Neuropsychological Tests},
author = {{M. Iglesias} and {A. Favaro} and {C. Motley} and {E. Oh} and {R. Stevens} and {A. Butala} and {L. Moro-Velázquez} and {N. Dehak}},
year = 2022,
month = {12},
booktitle = {IEEE Signal Processing in Medicine and Biology Symposium},
url = {https://www.semanticscholar.org/paper/ee067fbced756c332d18a34d6d4f59ab512f9013},
}

O. Ogundepo, X. Zhang, S. Sun, K. Duh, and J. Lin, “AfriCLIRMatrix: Enabling Cross-Lingual Information Retrieval for African Languages,” in Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, Abu Dhabi, United Arab Emirates, 2022, p. 8721–8728. doi:10.18653/v1/2022.emnlp-main.597
[BibTeX] [Abstract] [Link]

Language diversity in NLP is critical in enabling the development of tools for a wide range of users. However, there are limited resources for building such tools for many languages, particularly those spoken in Africa.For search, most existing datasets feature few or no African languages, directly impacting researchers{‘} ability to build and improve information access capabilities in those languages. Motivated by this, we created AfriCLIRMatrix, a test collection for cross-lingual information retrieval research in 15 diverse African languages. In total, our dataset contains 6 million queries in English and 23 million relevance judgments automatically mined from Wikipedia inter-language links, covering many more African languages than any existing information retrieval test collection. In addition, we release BM25, dense retrieval, and sparse{–}dense hybrid baselines to provide a starting point for the development of future systems. We hope that these efforts can spur additional work in search for African languages.AfriCLIRMatrix can be downloaded at \url{https://github.com/castorini/africlirmatrix}.

@inproceedings{ogundepo-etal-2022-africlirmatrix,
title = "{A}fri{CLIRM}atrix: Enabling Cross-Lingual Information Retrieval for {A}frican Languages",
author = "Ogundepo, Odunayo and
Zhang, Xinyu and
Sun, Shuo and
Duh, Kevin and
Lin, Jimmy",
editor = "Goldberg, Yoav and
Kozareva, Zornitsa and
Zhang, Yue",
booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.emnlp-main.597",
doi = "10.18653/v1/2022.emnlp-main.597",
pages = "8721--8728",
abstract = "Language diversity in NLP is critical in enabling the development of tools for a wide range of users. However, there are limited resources for building such tools for many languages, particularly those spoken in Africa.For search, most existing datasets feature few or no African languages, directly impacting researchers{'} ability to build and improve information access capabilities in those languages. Motivated by this, we created AfriCLIRMatrix, a test collection for cross-lingual information retrieval research in 15 diverse African languages. In total, our dataset contains 6 million queries in English and 23 million relevance judgments automatically mined from Wikipedia inter-language links, covering many more African languages than any existing information retrieval test collection. In addition, we release BM25, dense retrieval, and sparse{--}dense hybrid baselines to provide a starting point for the development of future systems. We hope that these efforts can spur additional work in search for African languages.AfriCLIRMatrix can be downloaded at \url{https://github.com/castorini/africlirmatrix}.",
}

S. Sia, K. Jaidka, H. Ahuja, N. Chhaya, and K. Duh, “Offer a Different Perspective: Modeling the Belief Alignment of Arguments in Multi-party Debates,” in Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, Abu Dhabi, United Arab Emirates, 2022, p. 11939–11950. doi:10.18653/v1/2022.emnlp-main.818
[BibTeX] [Abstract] [Link]

In contexts where debate and deliberation are the norm, the participants are regularly presented with new information that conflicts with their original beliefs. When required to update their beliefs (belief alignment), they may choose arguments that align with their worldview (confirmation bias). We test this and competing hypotheses in a constraint-based modeling approach to predict the winning arguments in multi-party interactions in the Reddit Change My View and Intelligence Squared debates datasets. We adopt a hierarchical generative Variational Autoencoder as our model and impose structural constraints that reflect competing hypotheses about the nature of argumentation. Our findings suggest that in most settings, predictive models that anticipate winning arguments to be further from the initial argument of the opinion holder are more likely to succeed.

@inproceedings{sia-etal-2022-offer,
title = "Offer a Different Perspective: Modeling the Belief Alignment of Arguments in Multi-party Debates",
author = "Sia, Suzanna and
Jaidka, Kokil and
Ahuja, Hansin and
Chhaya, Niyati and
Duh, Kevin",
editor = "Goldberg, Yoav and
Kozareva, Zornitsa and
Zhang, Yue",
booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.emnlp-main.818",
doi = "10.18653/v1/2022.emnlp-main.818",
pages = "11939--11950",
abstract = "In contexts where debate and deliberation are the norm, the participants are regularly presented with new information that conflicts with their original beliefs. When required to update their beliefs (belief alignment), they may choose arguments that align with their worldview (confirmation bias). We test this and competing hypotheses in a constraint-based modeling approach to predict the winning arguments in multi-party interactions in the Reddit Change My View and Intelligence Squared debates datasets. We adopt a hierarchical generative Variational Autoencoder as our model and impose structural constraints that reflect competing hypotheses about the nature of argumentation. Our findings suggest that in most settings, predictive models that anticipate winning arguments to be further from the initial argument of the opinion holder are more likely to succeed.",
}

A. Svete, B. Dayan, R. Cotterell, T. Vieira, and J. Eisner, “Acyclic Weighted Finite-State Automata with Failure Transitions,” in Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, Abu Dhabi, 2022, p. 8289–8305.
[BibTeX] [Link]

@InProceedings{svete-et-al-2022,
aclid = "2022.emnlp-main.567",
author = "Anej Svete and Benjamin Dayan and Ryan Cotterell and
Tim Vieira and Jason Eisner",
title = "Acyclic Weighted Finite-State Automata with Failure
Transitions",
booktitle = "Proceedings of the 2022 Conference on Empirical
Methods in Natural Language Processing",
pages = "8289--8305",
year = "2022",
month = dec,
address = "Abu Dhabi",
URL = "http://cs.jhu.edu/~jason/papers/#svete-et-al-2022",
}

E. Stengel-Eskin, E. A. Platanios, A. Pauls, S. Thomson, H. Fang, B. V. Durme, J. Eisner, and Y. Su, “When More Data Hurts: A Troubling Quirk in Developing Broad-Coverage Natural Language Understanding Systems,” in Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, Abu Dhabi, 2022, p. 11473–11487.
[BibTeX] [Link]

@InProceedings{stengeleskin-et-al-2022,
aclid = "2022.emnlp-main.789",
author = "Elias Stengel-Eskin and Emmanouil Antonios Platanios
and Adam Pauls and Sam Thomson and Hao Fang and
Benjamin Van Durme and Jason Eisner and Yu Su",
title = "When More Data Hurts: {A} Troubling Quirk in
Developing Broad-Coverage Natural Language
Understanding Systems",
booktitle = "Proceedings of the 2022 Conference on Empirical
Methods in Natural Language Processing",
pages = "11473--11487",
year = "2022",
month = dec,
address = "Abu Dhabi",
URL = "http://cs.jhu.edu/~jason/papers/#stengeleskin-et-al-2022",
}

Thanh Nguyen-Tang, Ming Yin, S. Gupta, S. Venkatesh, and R. Arora, “On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation,” in AAAI Conference on Artificial Intelligence, 2022.
[BibTeX] [Link]

@inproceedings{253801674,
title = {On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation},
author = {{Thanh Nguyen-Tang} and {Ming Yin} and {S. Gupta} and {S. Venkatesh} and {R. Arora}},
year = 2022,
month = {11},
booktitle = {AAAI Conference on Artificial Intelligence},
url = {https://www.semanticscholar.org/paper/b61a3d718a192e39a437d32a6ed4037b8c29cc41},
}

Yuxiang Guo, Cheng Peng, Chun Pong Lau, and R. Chellappa, “Multi-Modal Human Authentication Using Silhouettes, Gait and RGB,” in IEEE International Conference on Automatic Face & Gesture Recognition, 2022.
[BibTeX] [Link]

@inproceedings{252780362,
title = {Multi-Modal Human Authentication Using Silhouettes, Gait and RGB},
author = {{Yuxiang Guo} and {Cheng Peng} and {Chun Pong Lau} and {R. Chellappa}},
year = 2022,
month = {10},
booktitle = {IEEE International Conference on Automatic Face & Gesture Recognition},
url = {https://www.semanticscholar.org/paper/e89d9b5c7b5d9c4b490ba1d5fdbbca423920c3e1},
}

Chris Nalty, Neehar Peri, Joshua Gleason, C. Castillo, Shuowen Hu, T. Bourlai, and R. Chellappa, “A Brief Survey on Person Recognition at a Distance,” in Asilomar Conference on Signals, Systems and Computers, 2022.
[BibTeX] [Link]

@inproceedings{254853697,
title = {A Brief Survey on Person Recognition at a Distance},
author = {{Chris Nalty} and {Neehar Peri} and {Joshua Gleason} and {C. Castillo} and {Shuowen Hu} and {T. Bourlai} and {R. Chellappa}},
year = 2022,
month = {10},
booktitle = {Asilomar Conference on Signals, Systems and Computers},
url = {https://www.semanticscholar.org/paper/6934bd40d21e3bddce5328d29a7e1083e21d0aad},
}

S. Sia and K. Duh, “Prefix Embeddings for In-context Machine Translation,” in Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Volume 1: Research Track), Orlando, USA, 2022, p. 45–57.
[BibTeX] [Abstract] [Link]

Very large language models have been shown to translate with few-shot in-context examples. However, they have not achieved state-of-art results for translating out of English. In this work, we investigate an extremely lightweight fixed-parameter method for conditioning a large language model to better translate into the target language. Our method introduces additional embeddings, known as prefix embeddings which do not interfere with the existing weights of the model. Using unsupervised and weakly semi-supervised methods that train only 0.0001{\%} of the model parameters, the simple method improves {\textasciitilde}0.2-1.3 BLEU points across 3 domains and 3 languages. We analyze the resulting embeddings{‘} training dynamics, and where they lie in the embedding space, and show that our trained embeddings can be used for both in-context translation, and diverse generation of the target sentence.

@inproceedings{sia-duh-2022-prefix,
title = "Prefix Embeddings for In-context Machine Translation",
author = "Sia, Suzanna and
Duh, Kevin",
editor = "Duh, Kevin and
Guzm{\'a}n, Francisco",
booktitle = "Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Volume 1: Research Track)",
month = sep,
year = "2022",
address = "Orlando, USA",
publisher = "Association for Machine Translation in the Americas",
url = "https://aclanthology.org/2022.amta-research.4",
pages = "45--57",
abstract = "Very large language models have been shown to translate with few-shot in-context examples. However, they have not achieved state-of-art results for translating out of English. In this work, we investigate an extremely lightweight fixed-parameter method for conditioning a large language model to better translate into the target language. Our method introduces additional embeddings, known as prefix embeddings which do not interfere with the existing weights of the model. Using unsupervised and weakly semi-supervised methods that train only 0.0001{\%} of the model parameters, the simple method improves {\textasciitilde}0.2-1.3 BLEU points across 3 domains and 3 languages. We analyze the resulting embeddings{'} training dynamics, and where they lie in the embedding space, and show that our trained embeddings can be used for both in-context translation, and diverse generation of the target sentence.",
}

N. Verma, K. Murray, and K. Duh, “Strategies for Adapting Multilingual Pre-training for Domain-Specific Machine Translation,” in Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Volume 1: Research Track), Orlando, USA, 2022, p. 31–44.
[BibTeX] [Abstract] [Link]

Pretrained multilingual sequence-to-sequence models have been successful in improving translation performance for mid- and lower-resourced languages. However, it is unclear if these models are helpful in the domain adaptation setting, and if so, how to best adapt them to both the domain and translation language pair. Therefore, in this work, we propose two major fine-tuning strategies: our language-first approach first learns the translation language pair via general bitext, followed by the domain via in-domain bitext, and our domain-first approach first learns the domain via multilingual in-domain bitext, followed by the language pair via language pair-specific in-domain bitext. We test our approach on 3 domains at different levels of data availability, and 5 language pairs. We find that models using an mBART initialization generally outperform those using a random Transformer initialization. This holds for languages even outside of mBART{‘}s pretraining set, and can result in improvements of over +10 BLEU. Additionally, we find that via our domain-first approach, fine-tuning across multilingual in-domain corpora can lead to stark improvements in domain adaptation without sourcing additional out-of-domain bitext. In larger domain availability settings, our domain-first approach can be competitive with our language-first approach, even when using over 50X less data.

@inproceedings{verma-etal-2022-strategies,
title = "Strategies for Adapting Multilingual Pre-training for Domain-Specific Machine Translation",
author = "Verma, Neha and
Murray, Kenton and
Duh, Kevin",
editor = "Duh, Kevin and
Guzm{\'a}n, Francisco",
booktitle = "Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Volume 1: Research Track)",
month = sep,
year = "2022",
address = "Orlando, USA",
publisher = "Association for Machine Translation in the Americas",
url = "https://aclanthology.org/2022.amta-research.3",
pages = "31--44",
abstract = "Pretrained multilingual sequence-to-sequence models have been successful in improving translation performance for mid- and lower-resourced languages. However, it is unclear if these models are helpful in the domain adaptation setting, and if so, how to best adapt them to both the domain and translation language pair. Therefore, in this work, we propose two major fine-tuning strategies: our language-first approach first learns the translation language pair via general bitext, followed by the domain via in-domain bitext, and our domain-first approach first learns the domain via multilingual in-domain bitext, followed by the language pair via language pair-specific in-domain bitext. We test our approach on 3 domains at different levels of data availability, and 5 language pairs. We find that models using an mBART initialization generally outperform those using a random Transformer initialization. This holds for languages even outside of mBART{'}s pretraining set, and can result in improvements of over +10 BLEU. Additionally, we find that via our domain-first approach, fine-tuning across multilingual in-domain corpora can lead to stark improvements in domain adaptation without sourcing additional out-of-domain bitext. In larger domain availability settings, our domain-first approach can be competitive with our language-first approach, even when using over 50X less data.",
}

L. Kanashiro Pereira, “Attention-Focused Adversarial Training for Robust Temporal Reasoning,” in Proceedings of the Thirteenth Language Resources and Evaluation Conference, Marseille, France, 2022, p. 7352–7359.
[BibTeX] [Abstract] [Link]

We propose an enhanced adversarial training algorithm for fine-tuning transformer-based language models (i.e., RoBERTa) and apply it to the temporal reasoning task. Current adversarial training approaches for NLP add the adversarial perturbation only to the embedding layer, ignoring the other layers of the model, which might limit the generalization power of adversarial training. Instead, our algorithm searches for the best combination of layers to add the adversarial perturbation. We add the adversarial perturbation to multiple hidden states or attention representations of the model layers. Adding the perturbation to the attention representations performed best in our experiments. Our model can improve performance on several temporal reasoning benchmarks, and establishes new state-of-the-art results.

@inproceedings{kanashiro-pereira-2022-attention,
title = "Attention-Focused Adversarial Training for Robust Temporal Reasoning",
author = "Kanashiro Pereira, Lis",
editor = "Calzolari, Nicoletta and
B{\'e}chet, Fr{\'e}d{\'e}ric and
Blache, Philippe and
Choukri, Khalid and
Cieri, Christopher and
Declerck, Thierry and
Goggi, Sara and
Isahara, Hitoshi and
Maegaard, Bente and
Mariani, Joseph and
Mazo, H{\'e}l{\`e}ne and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference",
month = jun,
year = "2022",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2022.lrec-1.800",
pages = "7352--7359",
abstract = "We propose an enhanced adversarial training algorithm for fine-tuning transformer-based language models (i.e., RoBERTa) and apply it to the temporal reasoning task. Current adversarial training approaches for NLP add the adversarial perturbation only to the embedding layer, ignoring the other layers of the model, which might limit the generalization power of adversarial training. Instead, our algorithm searches for the best combination of layers to add the adversarial perturbation. We add the adversarial perturbation to multiple hidden states or attention representations of the model layers. Adding the perturbation to the attention representations performed best in our experiments. Our model can improve performance on several temporal reasoning benchmarks, and establishes new state-of-the-art results.",
}

A. Anastasopoulos, L. Barrault, L. Bentivogli, M. Zanon Boito, O. Bojar, R. Cattoni, A. Currey, G. Dinu, K. Duh, M. Elbayad, C. Emmanuel, Y. Estève, M. Federico, C. Federmann, S. Gahbiche, H. Gong, R. Grundkiewicz, B. Haddow, B. Hsu, D. Javorský, V. Kloudová, S. Lakew, X. Ma, P. Mathur, P. McNamee, K. Murray, M. N{v{a}}dejde, S. Nakamura, M. Negri, J. Niehues, X. Niu, J. Ortega, J. Pino, E. Salesky, J. Shi, M. Sperber, S. Stüker, K. Sudoh, M. Turchi, Y. Virkar, A. Waibel, C. Wang, and S. Watanabe, “Findings of the IWSLT 2022 Evaluation Campaign,” in Proceedings of the 19th International Conference on Spoken Language Translation (IWSLT 2022), Dublin, Ireland (in-person and online), 2022, p. 98–157. doi:10.18653/v1/2022.iwslt-1.10
[BibTeX] [Abstract] [Link]

The evaluation campaign of the 19th International Conference on Spoken Language Translation featured eight shared tasks: (i) Simultaneous speech translation, (ii) Offline speech translation, (iii) Speech to speech translation, (iv) Low-resource speech translation, (v) Multilingual speech translation, (vi) Dialect speech translation, (vii) Formality control for speech translation, (viii) Isometric speech translation. A total of 27 teams participated in at least one of the shared tasks. This paper details, for each shared task, the purpose of the task, the data that were released, the evaluation metrics that were applied, the submissions that were received and the results that were achieved.

@inproceedings{anastasopoulos-etal-2022-findings,
title = "Findings of the {IWSLT} 2022 Evaluation Campaign",
author = {Anastasopoulos, Antonios and
Barrault, Lo{\"\i}c and
Bentivogli, Luisa and
Zanon Boito, Marcely and
Bojar, Ond{\v{r}}ej and
Cattoni, Roldano and
Currey, Anna and
Dinu, Georgiana and
Duh, Kevin and
Elbayad, Maha and
Emmanuel, Clara and
Est{\`e}ve, Yannick and
Federico, Marcello and
Federmann, Christian and
Gahbiche, Souhir and
Gong, Hongyu and
Grundkiewicz, Roman and
Haddow, Barry and
Hsu, Benjamin and
Javorsk{\'y}, D{\'a}vid and
Kloudov{\'a}, V{\u{e}}ra and
Lakew, Surafel and
Ma, Xutai and
Mathur, Prashant and
McNamee, Paul and
Murray, Kenton and
N{\v{a}}dejde, Maria and
Nakamura, Satoshi and
Negri, Matteo and
Niehues, Jan and
Niu, Xing and
Ortega, John and
Pino, Juan and
Salesky, Elizabeth and
Shi, Jiatong and
Sperber, Matthias and
St{\"u}ker, Sebastian and
Sudoh, Katsuhito and
Turchi, Marco and
Virkar, Yogesh and
Waibel, Alexander and
Wang, Changhan and
Watanabe, Shinji},
editor = "Salesky, Elizabeth and
Federico, Marcello and
Costa-juss{\`a}, Marta",
booktitle = "Proceedings of the 19th International Conference on Spoken Language Translation (IWSLT 2022)",
month = may,
year = "2022",
address = "Dublin, Ireland (in-person and online)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.iwslt-1.10",
doi = "10.18653/v1/2022.iwslt-1.10",
pages = "98--157",
abstract = "The evaluation campaign of the 19th International Conference on Spoken Language Translation featured eight shared tasks: (i) Simultaneous speech translation, (ii) Offline speech translation, (iii) Speech to speech translation, (iv) Low-resource speech translation, (v) Multilingual speech translation, (vi) Dialect speech translation, (vii) Formality control for speech translation, (viii) Isometric speech translation. A total of 27 teams participated in at least one of the shared tasks. This paper details, for each shared task, the purpose of the task, the data that were released, the evaluation metrics that were applied, the submissions that were received and the results that were achieved.",
}

S. Wu, B. Van Durme, and M. Dredze, “Zero-shot Cross-lingual Transfer is Under-specified Optimization,” in Proceedings of the 7th Workshop on Representation Learning for NLP, Dublin, Ireland, 2022, p. 236–248. doi:10.18653/v1/2022.repl4nlp-1.25
[BibTeX] [Abstract] [Link]

Pretrained multilingual encoders enable zero-shot cross-lingual transfer, but often produce unreliable models that exhibit high performance variance on the target language. We postulate that this high variance results from zero-shot cross-lingual transfer solving an under-specified optimization problem. We show that any linear-interpolated model between the source language monolingual model and source + target bilingual model has equally low source language generalization error, yet the target language generalization error reduces smoothly and linearly as we move from the monolingual to bilingual model, suggesting that the model struggles to identify good solutions for both source and target languages using the source language alone. Additionally, we show that zero-shot solution lies in non-flat region of target language error generalization surface, causing the high variance.

@inproceedings{wu-etal-2022-zero,
title = "Zero-shot Cross-lingual Transfer is Under-specified Optimization",
author = "Wu, Shijie and
Van Durme, Benjamin and
Dredze, Mark",
editor = "Gella, Spandana and
He, He and
Majumder, Bodhisattwa Prasad and
Can, Burcu and
Giunchiglia, Eleonora and
Cahyawijaya, Samuel and
Min, Sewon and
Mozes, Maximilian and
Li, Xiang Lorraine and
Augenstein, Isabelle and
Rogers, Anna and
Cho, Kyunghyun and
Grefenstette, Edward and
Rimell, Laura and
Dyer, Chris",
booktitle = "Proceedings of the 7th Workshop on Representation Learning for NLP",
month = may,
year = "2022",
address = "Dublin, Ireland",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.repl4nlp-1.25",
doi = "10.18653/v1/2022.repl4nlp-1.25",
pages = "236--248",
abstract = "Pretrained multilingual encoders enable zero-shot cross-lingual transfer, but often produce unreliable models that exhibit high performance variance on the target language. We postulate that this high variance results from zero-shot cross-lingual transfer solving an under-specified optimization problem. We show that any linear-interpolated model between the source language monolingual model and source + target bilingual model has equally low source language generalization error, yet the target language generalization error reduces smoothly and linearly as we move from the monolingual to bilingual model, suggesting that the model struggles to identify good solutions for both source and target languages using the source language alone. Additionally, we show that zero-shot solution lies in non-flat region of target language error generalization surface, causing the high variance.",
}

S. Panthaplackel, A. Benton, and M. Dredze, “Updated Headline Generation: Creating Updated Summaries for Evolving News Stories,” in Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Dublin, Ireland, 2022, p. 6438–6461. doi:10.18653/v1/2022.acl-long.446
[BibTeX] [Abstract] [Link]

We propose the task of updated headline generation, in which a system generates a headline for an updated article, considering both the previous article and headline. The system must identify the novel information in the article update, and modify the existing headline accordingly. We create data for this task using the NewsEdits corpus by automatically identifying contiguous article versions that are likely to require a substantive headline update. We find that models conditioned on the prior headline and body revisions produce headlines judged by humans to be as factual as gold headlines while making fewer unnecessary edits compared to a standard headline generation model. Our experiments establish benchmarks for this new contextual summarization task.

@inproceedings{panthaplackel-etal-2022-updated,
title = "Updated Headline Generation: Creating Updated Summaries for Evolving News Stories",
author = "Panthaplackel, Sheena and
Benton, Adrian and
Dredze, Mark",
editor = "Muresan, Smaranda and
Nakov, Preslav and
Villavicencio, Aline",
booktitle = "Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = may,
year = "2022",
address = "Dublin, Ireland",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.acl-long.446",
doi = "10.18653/v1/2022.acl-long.446",
pages = "6438--6461",
abstract = "We propose the task of updated headline generation, in which a system generates a headline for an updated article, considering both the previous article and headline. The system must identify the novel information in the article update, and modify the existing headline accordingly. We create data for this task using the NewsEdits corpus by automatically identifying contiguous article versions that are likely to require a substantive headline update. We find that models conditioned on the prior headline and body revisions produce headlines judged by humans to be as factual as gold headlines while making fewer unnecessary edits compared to a standard headline generation model. Our experiments establish benchmarks for this new contextual summarization task.",
}

J. Zhou, J. Eisner, M. Newman, E. A. Platanios, and S. Thomson, “Online Semantic Parsing for Latency Reduction in Task-Oriented Dialogue,” in Proceedings of the Association for Computational Linguistics (ACL), Dublin, 2022, p. 1554–1576. doi:10.18653/v1/2022.acl-long.110
[BibTeX] [Link]

@InProceedings{zhou-et-al-2022,
aclid = "2022.acl-long.110",
doi = "10.18653/v1/2022.acl-long.110",
author = "Jiawei Zhou and Jason Eisner and Michael Newman and
Emmanouil Anthony Platanios and Sam Thomson",
title = "Online Semantic Parsing for Latency Reduction in
Task-Oriented Dialogue",
booktitle = "Proceedings of the Association for Computational
Linguistics (ACL)",
pages = "1554--1576",
year = "2022",
month = may,
address = "Dublin",
URL = "http://cs.jhu.edu/~jason/papers/#zhou-et-al-2022",
}

R. Cotterell and J. Eisner, “A Functionalist Account of Vowel System Typology,” in Proceedings of the Association for Computational Linguistics (ACL), Dublin, 2022.
[BibTeX] [Link]

@InProceedings{cotterell-eisner-2022,
author = "Ryan Cotterell and Jason Eisner",
title = "A Functionalist Account of Vowel System Typology",
booktitle = "Proceedings of the Association for Computational
Linguistics (ACL)",
year = "2022",
month = may,
address = "Dublin",
note = "Paper was accepted, but we withdrew it in order to add
more experiments and analysis before publication.",
URL = "http://cs.jhu.edu/~jason/papers/#cotterell-eisner-2022",
}

C. Yang, H. Mei, and J. Eisner, “Transformer Embeddings of Irregularly Spaced Events and Their Participants,” in Proceedings of the Tenth International Conference on Learning Representations (ICLR), 2022.
[BibTeX] [Link]

@InProceedings{yang-et-al-2022-iclr,
author = "Chenghao Yang and Hongyuan Mei and Jason Eisner",
title = "Transformer Embeddings of Irregularly Spaced Events
and Their Participants",
booktitle = "Proceedings of the Tenth International Conference on
Learning Representations (ICLR)",
year = "2022",
month = apr,
note = "9 pages plus appendices",
URL = "http://cs.jhu.edu/~jason/papers/#yang-et-al-2022-iclr",
}

Amir Alipour-Fanid, Monireh Dabaghchian, R. Arora, and K. Zeng, “Multiuser Scheduling in Centralized Cognitive Radio Networks: A Multi-Armed Bandit Approach,” in IEEE Transactions on Cognitive Communications and Networking, 2022.
[BibTeX] [Link]

@inproceedings{246595318,
title = {Multiuser Scheduling in Centralized Cognitive Radio Networks: A Multi-Armed Bandit Approach},
author = {{Amir Alipour-Fanid} and {Monireh Dabaghchian} and {R. Arora} and {K. Zeng}},
year = 2022,
month = {6},
booktitle = {IEEE Transactions on Cognitive Communications and Networking},
url = {https://www.semanticscholar.org/paper/ad0c8cc0a80c5873591e62ca9f47fa21b631c35f},
}

Saksham Suri, Saketh Rambhatla, R. Chellappa, and Abhinav Shrivastava, “R-SSL: Region based Semi-Supervised Learning for Sparsely Annotated Object Detection.” 2022.
[BibTeX] [Link]

@inproceedings{255750913,
title = {R-SSL: Region based Semi-Supervised Learning for Sparsely Annotated Object Detection},
author = {{Saksham Suri} and {Saketh Rambhatla} and {R. Chellappa} and {Abhinav Shrivastava}},
year = 2022,
booktitle = {},
url = {https://www.semanticscholar.org/paper/e2e159205030b9d3e3d742b4bdbebd7e94201d3f},
}

R. Arora, Raef Bassily, Tom’as Gonz’alez, Crist’obal Guzm’an, Michael Menart, and Enayat Ullah, “Faster Rates of Convergence to Stationary Points in Differentially Private Optimization,” in International Conference on Machine Learning, 2022.
[BibTeX] [Link]

@inproceedings{249282662,
title = {Faster Rates of Convergence to Stationary Points in Differentially Private Optimization},
author = {{R. Arora} and {Raef Bassily} and {Tom'as Gonz'alez} and {Crist'obal Guzm'an} and {Michael Menart} and {Enayat Ullah}},
year = 2022,
month = {6},
booktitle = {International Conference on Machine Learning},
url = {https://www.semanticscholar.org/paper/6f85ad4e04fc157ed5b499e348972f188a39cd10},
}

Sonal Joshi, Saurabh Kataria, Yiwen Shao, Piotr Żelasko, J. Villalba, S. Khudanpur, and N. Dehak, “Defense against Adversarial Attacks on Hybrid Speech Recognition using Joint Adversarial Fine-tuning with Denoiser,” in arXiv.org, 2022.
[BibTeX] [Link]

@inproceedings{248069341,
title = {Defense against Adversarial Attacks on Hybrid Speech Recognition using Joint Adversarial Fine-tuning with Denoiser},
author = {{Sonal Joshi} and {Saurabh Kataria} and {Yiwen Shao} and {Piotr Żelasko} and {J. Villalba} and {S. Khudanpur} and {N. Dehak}},
year = 2022,
month = {4},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/49011d1b139bbb65fe273fd9e4b2197cee237385},
}

Saurabh Kataria, J. Villalba, Laureano Moro-Vel’azquez, and N. Dehak, “Joint domain adaptation and speech bandwidth extension using time-domain GANs for speaker verification,” in Interspeech, 2022.
[BibTeX] [Link]

@inproceedings{247839251,
title = {Joint domain adaptation and speech bandwidth extension using time-domain GANs for speaker verification},
author = {{Saurabh Kataria} and {J. Villalba} and {Laureano Moro-Vel'azquez} and {N. Dehak}},
year = 2022,
month = {3},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/d58ebbc34e8ea987da5dda1bb132823b3e9105d3},
}

Shraman Pramanick, E. Nowara, Joshua Gleason, C. Castillo, and R. Chellappa, “Where in the World is this Image? Transformer-based Geo-localization in the Wild,” in European Conference on Computer Vision, 2022.
[BibTeX] [Link]

@inproceedings{248476325,
title = {Where in the World is this Image? Transformer-based Geo-localization in the Wild},
author = {{Shraman Pramanick} and {E. Nowara} and {Joshua Gleason} and {C. Castillo} and {R. Chellappa}},
year = 2022,
month = {4},
booktitle = {European Conference on Computer Vision},
url = {https://www.semanticscholar.org/paper/1889dfb7c30f2b9f8e9d4026ca71ec10caa449af},
}

Suraj Nair, Eugene Yang, Dawn J Lawrie, Kevin Duh, Paul McNamee, Kenton Murray, J. Mayfield, and Douglas W. Oard, “Transfer Learning Approaches for Building Cross-Language Dense Retrieval Models,” in European Conference on Information Retrieval, 2022.
[BibTeX] [Link]

@inproceedings{246210468,
title = {Transfer Learning Approaches for Building Cross-Language Dense Retrieval Models},
author = {{Suraj Nair} and {Eugene Yang} and {Dawn J Lawrie} and {Kevin Duh} and {Paul McNamee} and {Kenton Murray} and {J. Mayfield} and {Douglas W. Oard}},
year = 2022,
month = {1},
booktitle = {European Conference on Information Retrieval},
url = {https://www.semanticscholar.org/paper/d1ccffb8eb1b7a99cd586723074b82fa5399bdd2},
}

Sonal Joshi, Saurabh Kataria, J. Villalba, and N. Dehak, “AdvEst: Adversarial Perturbation Estimation to Classify and Detect Adversarial Attacks against Speaker Identification,” in Interspeech, 2022.
[BibTeX] [Link]

@inproceedings{248069457,
title = {AdvEst: Adversarial Perturbation Estimation to Classify and Detect Adversarial Attacks against Speaker Identification},
author = {{Sonal Joshi} and {Saurabh Kataria} and {J. Villalba} and {N. Dehak}},
year = 2022,
month = {4},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/a8144dbb8481cb78e08fc34e452603984bb5aa01},
}

Jaejin Cho, R. Pappagari, Piotr Żelasko, L. Moro-Velázquez, J. Villalba, and N. Dehak, “Non-Contrastive Self-Supervised Learning of Utterance-Level Speech Representations,” in Interspeech, 2022.
[BibTeX] [Link]

@inproceedings{251468156,
title = {Non-Contrastive Self-Supervised Learning of Utterance-Level Speech Representations},
author = {{Jaejin Cho} and {R. Pappagari} and {Piotr Żelasko} and {L. Moro-Velázquez} and {J. Villalba} and {N. Dehak}},
year = 2022,
month = {8},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/f3d7789c627d3e62d92c225a272e408f287c6317},
}

Sai Saketh Rambhatla, Saksham Suri, R. Chellappa, and Abhinav Shrivastava, “SparseDet: Improving Sparsely Annotated Object Detection with Pseudo-positive Mining,” in IEEE International Conference on Computer Vision, 2022.
[BibTeX] [Link]

@inproceedings{245877805,
title = {SparseDet: Improving Sparsely Annotated Object Detection with Pseudo-positive Mining},
author = {{Sai Saketh Rambhatla} and {Saksham Suri} and {R. Chellappa} and {Abhinav Shrivastava}},
year = 2022,
month = {1},
booktitle = {IEEE International Conference on Computer Vision},
url = {https://www.semanticscholar.org/paper/7f71d5804fe434168643babc616a76eb65d5882e},
}

K. Deb, X. Zhang, and K. Duh, “Post-Hoc Interpretation of Transformer Hyperparameters with Explainable Boosting Machines,” in Proceedings of the Fifth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, Abu Dhabi, United Arab Emirates (Hybrid), 2022, p. 51–61. doi:10.18653/v1/2022.blackboxnlp-1.5
[BibTeX] [Abstract] [Link]

Hyperparameter tuning is important for achieving high accuracy in deep learning models, yet little interpretability work has focused on hyperparameters. We propose to use the Explainable Boosting Machine (EBM), a glassbox method, as a post-hoc analysis tool for understanding how hyperparameters influence model accuracy. We present a case study on Transformer models in machine translation to illustrate the kinds of insights that may be gleaned, and perform extensive analysis to test the robustness of EBM under different data conditions.

@inproceedings{deb-etal-2022-post,
title = "Post-Hoc Interpretation of Transformer Hyperparameters with Explainable Boosting Machines",
author = "Deb, Kiron and
Zhang, Xuan and
Duh, Kevin",
editor = "Bastings, Jasmijn and
Belinkov, Yonatan and
Elazar, Yanai and
Hupkes, Dieuwke and
Saphra, Naomi and
Wiegreffe, Sarah",
booktitle = "Proceedings of the Fifth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates (Hybrid)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.blackboxnlp-1.5",
doi = "10.18653/v1/2022.blackboxnlp-1.5",
pages = "51--61",
abstract = "Hyperparameter tuning is important for achieving high accuracy in deep learning models, yet little interpretability work has focused on hyperparameters. We propose to use the Explainable Boosting Machine (EBM), a glassbox method, as a post-hoc analysis tool for understanding how hyperparameters influence model accuracy. We present a case study on Transformer models in machine translation to illustrate the kinds of insights that may be gleaned, and perform extensive analysis to test the robustness of EBM under different data conditions.",
}

P. McNamee and K. Duh, “The Multilingual Microblog Translation Corpus: Improving and Evaluating Translation of User-Generated Text,” in Proceedings of the Thirteenth Language Resources and Evaluation Conference, Marseille, France, 2022, p. 910–918.
[BibTeX] [Abstract] [Link]

Translation of the noisy, informal language found in social media has been an understudied problem, with a principal factor being the limited availability of translation corpora in many languages. To address this need we have developed a new corpus containing over 200,000 translations of microblog posts that supports translation of thirteen languages into English. The languages are: Arabic, Chinese, Farsi, French, German, Hindi, Korean, Pashto, Portuguese, Russian, Spanish, Tagalog, and Urdu. We are releasing these data as the Multilingual Microblog Translation Corpus to support futher research in translation of informal language. We establish baselines using this new resource, and we further demonstrate the utility of the corpus by conducting experiments with fine-tuning to improve translation quality from a high performing neural machine translation (NMT) system. Fine-tuning provided substantial gains, ranging from +3.4 to +11.1 BLEU. On average, a relative gain of 21{\%} was observed, demonstrating the utility of the corpus.

@inproceedings{mcnamee-duh-2022-multilingual,
title = "The Multilingual Microblog Translation Corpus: Improving and Evaluating Translation of User-Generated Text",
author = "McNamee, Paul and
Duh, Kevin",
editor = "Calzolari, Nicoletta and
B{\'e}chet, Fr{\'e}d{\'e}ric and
Blache, Philippe and
Choukri, Khalid and
Cieri, Christopher and
Declerck, Thierry and
Goggi, Sara and
Isahara, Hitoshi and
Maegaard, Bente and
Mariani, Joseph and
Mazo, H{\'e}l{\`e}ne and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference",
month = jun,
year = "2022",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2022.lrec-1.96",
pages = "910--918",
abstract = "Translation of the noisy, informal language found in social media has been an understudied problem, with a principal factor being the limited availability of translation corpora in many languages. To address this need we have developed a new corpus containing over 200,000 translations of microblog posts that supports translation of thirteen languages into English. The languages are: Arabic, Chinese, Farsi, French, German, Hindi, Korean, Pashto, Portuguese, Russian, Spanish, Tagalog, and Urdu. We are releasing these data as the Multilingual Microblog Translation Corpus to support futher research in translation of informal language. We establish baselines using this new resource, and we further demonstrate the utility of the corpus by conducting experiments with fine-tuning to improve translation quality from a high performing neural machine translation (NMT) system. Fine-tuning provided substantial gains, ranging from +3.4 to +11.1 BLEU. On average, a relative gain of 21{\%} was observed, demonstrating the utility of the corpus.",
}

Christos Sapsanis, M. Villemur, and A. Andreou, “Real Number Modeling of a SAR ADC behavior using SystemVerilog,” in International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design, 2022.
[BibTeX] [Link]

@inproceedings{250463643,
title = {Real Number Modeling of a SAR ADC behavior using SystemVerilog},
author = {{Christos Sapsanis} and {M. Villemur} and {A. Andreou}},
year = 2022,
month = {6},
booktitle = {International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design},
url = {https://www.semanticscholar.org/paper/528b50e00ed3efece80bbc4557ecf4f8df98094a},
}

Saurabh Kataria, J. Villalba, Laureano Moro-Vel’azquez, Piotr Żelasko, and N. Dehak, “Time-Domain Speech Super-Resolution With GAN Based Modeling for Telephony Speaker Verification,” in IEEE/ACM Transactions on Audio Speech and Language Processing, 2022.
[BibTeX] [Link]

@inproceedings{252090174,
title = {Time-Domain Speech Super-Resolution With GAN Based Modeling for Telephony Speaker Verification},
author = {{Saurabh Kataria} and {J. Villalba} and {Laureano Moro-Vel'azquez} and {Piotr Żelasko} and {N. Dehak}},
year = 2022,
month = {9},
booktitle = {IEEE/ACM Transactions on Audio Speech and Language Processing},
url = {https://www.semanticscholar.org/paper/312a44c9d2d2719ca8d3eb22539edd215415229e},
}

Suzanna Sia, Kokil Jaidka, Niyati Chayya, and Kevin Duh, “Modeling Constraints Can Identify Winning Arguments in Multi-Party Interactions (Student Abstract),” in AAAI Conference on Artificial Intelligence, 2022.
[BibTeX] [Link]

@inproceedings{250298720,
title = {Modeling Constraints Can Identify Winning Arguments in Multi-Party Interactions (Student Abstract)},
author = {{Suzanna Sia} and {Kokil Jaidka} and {Niyati Chayya} and {Kevin Duh}},
year = 2022,
month = {6},
booktitle = {AAAI Conference on Artificial Intelligence},
url = {https://www.semanticscholar.org/paper/da88a7e2b2187fc230b61f36752dbf396be9ce32},
}

Magdalena Rybicka, J. Villalba, N. Dehak, and K. Kowalczyk, “End-to-End Neural Speaker Diarization with an Iterative Refinement of Non-Autoregressive Attention-based Attractors,” in Interspeech, 2022.
[BibTeX] [Link]

@inproceedings{252346611,
title = {End-to-End Neural Speaker Diarization with an Iterative Refinement of Non-Autoregressive Attention-based Attractors},
author = {{Magdalena Rybicka} and {J. Villalba} and {N. Dehak} and {K. Kowalczyk}},
year = 2022,
month = {9},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/916cfa98c48af9931559fe0d8953bcaf7bdf7f2c},
}

Pirazh Khorramshahi, Vineet Shenoy, and R. Chellappa, “Scalable Vehicle Re-Identification via Self-Supervision,” in arXiv.org, 2022.
[BibTeX] [Link]

@inproceedings{248811372,
title = {Scalable Vehicle Re-Identification via Self-Supervision},
author = {{Pirazh Khorramshahi} and {Vineet Shenoy} and {R. Chellappa}},
year = 2022,
month = {5},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/9d69f0b6c916ac36e2bf28491d27c653eae245cd},
}

M. Villemur, Jonah P. Sengupta, P. Julián, and A. Andreou, “Morphological, Object Detection Framework for Embedded, Event-based Sensing,” in International Conference on Event-Based Control, Communication, and Signal Processing, 2022.
[BibTeX] [Link]

@inproceedings{251762249,
title = {Morphological, Object Detection Framework for Embedded, Event-based Sensing},
author = {{M. Villemur} and {Jonah P. Sengupta} and {P. Julián} and {A. Andreou}},
year = 2022,
month = {6},
booktitle = {International Conference on Event-Based Control, Communication, and Signal Processing},
url = {https://www.semanticscholar.org/paper/dc774c02c8260a15a0098b2a193b7b5db7e3fdb1},
}

Yiwen Shao, J. Villalba, Sonal Joshi, Saurabh Kataria, S. Khudanpur, and N. Dehak, “Chunking Defense for Adversarial Attacks on ASR,” in Interspeech, 2022.
[BibTeX] [Link]

@inproceedings{252341100,
title = {Chunking Defense for Adversarial Attacks on ASR},
author = {{Yiwen Shao} and {J. Villalba} and {Sonal Joshi} and {Saurabh Kataria} and {S. Khudanpur} and {N. Dehak}},
year = 2022,
month = {9},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/ace27d0f6e93765439e19203e69570cf00f09e63},
}

Piotr Żelasko, Siyuan Feng, Laureano Moro Velázquez, A. Abavisani, Saurabhchand Bhati, O. Scharenborg, M. Hasegawa-Johnson, and N. Dehak, “Discovering Phonetic Inventories with Crosslingual Automatic Speech Recognition,” in Computer Speech and Language, 2022.
[BibTeX] [Link]

@inproceedings{246294754,
title = {Discovering Phonetic Inventories with Crosslingual Automatic Speech Recognition},
author = {{Piotr Żelasko} and {Siyuan Feng} and {Laureano Moro Velázquez} and {A. Abavisani} and {Saurabhchand Bhati} and {O. Scharenborg} and {M. Hasegawa-Johnson} and {N. Dehak}},
year = 2022,
month = {1},
booktitle = {Computer Speech and Language},
url = {https://www.semanticscholar.org/paper/9da09ca7192a7546728575b2c0dfb923a36f110f},
}

Christos Sapsanis, M. Sophocleous, A. Andreou, and J. Georgiou, “Trade-Offs in Sensor Systems Design: A Tutorial,” in IEEE Sensors Journal, 2022.
[BibTeX] [Link]

@inproceedings{246805990,
title = {Trade-Offs in Sensor Systems Design: A Tutorial},
author = {{Christos Sapsanis} and {M. Sophocleous} and {A. Andreou} and {J. Georgiou}},
year = 2022,
month = {6},
booktitle = {IEEE Sensors Journal},
url = {https://www.semanticscholar.org/paper/07cfa0c80e6ef73a2aa5fab377c2f698ed476341},
}

Harminder Singh, R. Sharma, and R. Arora, “A Novel Dual-band filtenna for 2.4 and 5.8 GHz Wireless Local Area for Network Applications,” in 2022 Interdisciplinary Research in Technology and Management (IRTM), 2022.
[BibTeX] [Link]

@inproceedings{249795778,
title = {A Novel Dual-band filtenna for 2.4 and 5.8 GHz Wireless Local Area for Network Applications},
author = {{Harminder Singh} and {R. Sharma} and {R. Arora}},
year = 2022,
month = {2},
booktitle = {2022 Interdisciplinary Research in Technology and Management (IRTM)},
url = {https://www.semanticscholar.org/paper/a773c6edcc796c34a4cd477d6a39043cab45d037},
}

A. Hussein, S. A. Chowdhury, Ahmed Abdelali, N. Dehak, and Ahmed M. Ali, “Code-Switching Text Augmentation for Multilingual Speech Processing,” in arXiv.org, 2022.
[BibTeX] [Link]

@inproceedings{245827791,
title = {Code-Switching Text Augmentation for Multilingual Speech Processing},
author = {{A. Hussein} and {S. A. Chowdhury} and {Ahmed Abdelali} and {N. Dehak} and {Ahmed M. Ali}},
year = 2022,
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/be5074a85ef8166fc173cb51971a2e3f79685134},
}

Jonah P. Sengupta, M. Villemur, P. Pouliquen, P. Julián, and A. Andreou, “Embedded Processing Pipeline Exploration For Neuromorphic Event Based Perceptual Systems,” in International Symposium on Circuits and Systems, 2022.
[BibTeX] [Link]

@inproceedings{253461961,
title = {Embedded Processing Pipeline Exploration For Neuromorphic Event Based Perceptual Systems},
author = {{Jonah P. Sengupta} and {M. Villemur} and {P. Pouliquen} and {P. Julián} and {A. Andreou}},
year = 2022,
month = {5},
booktitle = {International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/42845a69a8efd8e8dc7b697c3ce0a4a8f6dfae86},
}

J. Villalba, B. J. Borgstrom, Saurabh Kataria, Jaejin Cho, P. Torres-Carrasquillo, and N. Dehak, “Advances in Speaker Recognition for Multilingual Conversational Telephone Speech: The JHU-MIT System for NIST SRE20 CTS Challenge,” in The Speaker and Language Recognition Workshop, 2022.
[BibTeX] [Link]

@inproceedings{249830266,
title = {Advances in Speaker Recognition for Multilingual Conversational Telephone Speech: The JHU-MIT System for NIST SRE20 CTS Challenge},
author = {{J. Villalba} and {B. J. Borgstrom} and {Saurabh Kataria} and {Jaejin Cho} and {P. Torres-Carrasquillo} and {N. Dehak}},
year = 2022,
month = {6},
booktitle = {The Speaker and Language Recognition Workshop},
url = {https://www.semanticscholar.org/paper/042e35459f6dfd8ad8be0dad72ae27f8e73cd4a8},
}

Xiaolei Huang, Franck Dernoncourt, and Mark Dredze, “Enriching Unsupervised User Embedding via Medical Concepts,” in ACM Conference on Health, Inference, and Learning, 2022.
[BibTeX] [Link]

@inproceedings{247594586,
title = {Enriching Unsupervised User Embedding via Medical Concepts},
author = {{Xiaolei Huang} and {Franck Dernoncourt} and {Mark Dredze}},
year = 2022,
month = {3},
booktitle = {ACM Conference on Health, Inference, and Learning},
url = {https://www.semanticscholar.org/paper/78a4f90b348f5401e8fb6b84bca0e539142b2530},
}

Pirazh Khorramshahi, Vineet Shenoy, M. Pack, and R. Chellappa, “Scalable and Real-time Multi-Camera Vehicle Detection, Re-Identification, and Tracking,” in arXiv.org, 2022.
[BibTeX] [Link]

@inproceedings{248218560,
title = {Scalable and Real-time Multi-Camera Vehicle Detection, Re-Identification, and Tracking},
author = {{Pirazh Khorramshahi} and {Vineet Shenoy} and {M. Pack} and {R. Chellappa}},
year = 2022,
month = {4},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/0babd241088a1d84dec824c9749c93a3e20fd583},
}

A. Hussein, S. A. Chowdhury, Ahmed Abdelali, N. Dehak, Ahmed M. Ali, and S. Khudanpur, “Textual Data Augmentation for Arabic-English Code-Switching Speech Recognition,” in Spoken Language Technology Workshop, 2022.
[BibTeX] [Link]

@inproceedings{255595965,
title = {Textual Data Augmentation for Arabic-English Code-Switching Speech Recognition},
author = {{A. Hussein} and {S. A. Chowdhury} and {Ahmed Abdelali} and {N. Dehak} and {Ahmed M. Ali} and {S. Khudanpur}},
year = 2022,
month = {1},
booktitle = {Spoken Language Technology Workshop},
url = {https://www.semanticscholar.org/paper/3c00e6cc82b49f046b5f36e5d5f8aa4af68cad5a},
}

Jaejin Cho, J. Villalba, L. Moro-Velázquez, and N. Dehak, “Non-Contrastive Self-Supervised Learning for Utterance-Level Information Extraction From Speech,” in IEEE Journal on Selected Topics in Signal Processing, 2022.
[BibTeX] [Link]

@inproceedings{251462729,
title = {Non-Contrastive Self-Supervised Learning for Utterance-Level Information Extraction From Speech},
author = {{Jaejin Cho} and {J. Villalba} and {L. Moro-Velázquez} and {N. Dehak}},
year = 2022,
month = {8},
booktitle = {IEEE Journal on Selected Topics in Signal Processing},
url = {https://www.semanticscholar.org/paper/7504aeee4c344c4cf9c6fc071dcc4b4b34d124cc},
}

R. Arora, Raef Bassily, Crist’obal Guzm’an, Michael Menart, and Enayat Ullah, “Differentially Private Generalized Linear Models Revisited,” in Neural Information Processing Systems, 2022.
[BibTeX] [Link]

@inproceedings{248562546,
title = {Differentially Private Generalized Linear Models Revisited},
author = {{R. Arora} and {Raef Bassily} and {Crist'obal Guzm'an} and {Michael Menart} and {Enayat Ullah}},
year = 2022,
month = {5},
booktitle = {Neural Information Processing Systems},
url = {https://www.semanticscholar.org/paper/7c8634be409d59c15b717cc1dc8f696289617e89},
}

Jared Markowitz, Ryan W. Gardner, Ashley J. Llorens, R. Arora, and I-J. Wang, “A Risk-Sensitive Approach to Policy Optimization,” in AAAI Conference on Artificial Intelligence, 2022.
[BibTeX] [Link]

@inproceedings{251710281,
title = {A Risk-Sensitive Approach to Policy Optimization},
author = {{Jared Markowitz} and {Ryan W. Gardner} and {Ashley J. Llorens} and {R. Arora} and {I-J. Wang}},
year = 2022,
month = {8},
booktitle = {AAAI Conference on Artificial Intelligence},
url = {https://www.semanticscholar.org/paper/2a1b41221def527e17eb1ca04f4f32442fa09ba7},
}

J. Zhang, A. DeLucia, and M. Dredze, “Changes in Tweet Geolocation over Time: A Study with Carmen 2.0,” in Proceedings of the Eighth Workshop on Noisy User-generated Text (W-NUT 2022), Gyeongju, Republic of Korea, 2022, p. 1–14.
[BibTeX] [Abstract] [Link]

Researchers across disciplines use Twitter geolocation tools to filter data for desired locations. These tools have largely been trained and tested on English tweets, often originating in the United States from almost a decade ago. Despite the importance of these tools for data curation, the impact of tweet language, country of origin, and creation date on tool performance remains largely unknown. We explore these issues with Carmen, a popular tool for Twitter geolocation. To support this study we introduce Carmen 2.0, a major update which includes the incorporation of GeoNames, a gazetteer that provides much broader coverage of locations. We evaluate using two new Twitter datasets, one for multilingual, multiyear geolocation evaluation, and another for usage trends over time. We found that language, country origin, and time does impact geolocation tool performance.

@inproceedings{zhang-etal-2022-changes,
title = "Changes in Tweet Geolocation over Time: A Study with Carmen 2.0",
author = "Zhang, Jingyu and
DeLucia, Alexandra and
Dredze, Mark",
booktitle = "Proceedings of the Eighth Workshop on Noisy User-generated Text (W-NUT 2022)",
month = oct,
year = "2022",
address = "Gyeongju, Republic of Korea",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.wnut-1.1",
pages = "1--14",
abstract = "Researchers across disciplines use Twitter geolocation tools to filter data for desired locations. These tools have largely been trained and tested on English tweets, often originating in the United States from almost a decade ago. Despite the importance of these tools for data curation, the impact of tweet language, country of origin, and creation date on tool performance remains largely unknown. We explore these issues with Carmen, a popular tool for Twitter geolocation. To support this study we introduce Carmen 2.0, a major update which includes the incorporation of GeoNames, a gazetteer that provides much broader coverage of locations. We evaluate using two new Twitter datasets, one for multilingual, multiyear geolocation evaluation, and another for usage trends over time. We found that language, country origin, and time does impact geolocation tool performance.",
}

Yunjuan Wang, Enayat Ullah, Poorya Mianjy, and R. Arora, “Adversarial Robustness is at Odds with Lazy Training,” in Neural Information Processing Systems, 2022.
[BibTeX] [Link]

@inproceedings{250243820,
title = {Adversarial Robustness is at Odds with Lazy Training},
author = {{Yunjuan Wang} and {Enayat Ullah} and {Poorya Mianjy} and {R. Arora}},
year = 2022,
month = {6},
booktitle = {Neural Information Processing Systems},
url = {https://www.semanticscholar.org/paper/e2100da66c556f6ce3fbe904696fb0cec2aca2bf},
}

Cheng Peng and R. Chellappa, “PDRF: Progressively Deblurring Radiance Field for Fast and Robust Scene Reconstruction from Blurry Images,” in AAAI Conference on Artificial Intelligence, 2022.
[BibTeX] [Link]

@inproceedings{251622408,
title = {PDRF: Progressively Deblurring Radiance Field for Fast and Robust Scene Reconstruction from Blurry Images},
author = {{Cheng Peng} and {R. Chellappa}},
year = 2022,
month = {8},
booktitle = {AAAI Conference on Artificial Intelligence},
url = {https://www.semanticscholar.org/paper/c900f690fdab5d17b0253d4362e7f1a7d9d2d495},
}

J. Sadeghi, Kevin Duh, G. Sugiyama, V. Patel, G. Coppa, and R. Barrera, “Pre-hospital caloric deficits in surgical patients.,” in Nutrition and Health, 2022.
[BibTeX] [Link]

@inproceedings{208391943,
title = {Pre-hospital caloric deficits in surgical patients.},
author = {{J. Sadeghi} and {Kevin Duh} and {G. Sugiyama} and {V. Patel} and {G. Coppa} and {R. Barrera}},
year = 2022,
month = {7},
booktitle = {Nutrition and Health},
url = {https://www.semanticscholar.org/paper/cfee21939b8a016ed3d947607940dc9a0ccf8b0c},
}

M. Naphade, Shuo Wang, D. Anastasiu, Zheng Tang, Ming-Ching Chang, Xiaodong Yang, Liang Zheng, Anuj Sharma, R. Chellappa, and Pranamesh Chakraborty, “The 6th AI City Challenge,” in 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2022.
[BibTeX] [Link]

@inproceedings{216914509,
title = {The 6th AI City Challenge},
author = {{M. Naphade} and {Shuo Wang} and {D. Anastasiu} and {Zheng Tang} and {Ming-Ching Chang} and {Xiaodong Yang} and {Liang Zheng} and {Anuj Sharma} and {R. Chellappa} and {Pranamesh Chakraborty}},
year = 2022,
month = {4},
booktitle = {2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
url = {https://www.semanticscholar.org/paper/7f489232a16a54fa2b11d5758101f078f9db797c},
}

R. Wicks and K. Duh, “The Effects of Language Token Prefixing for Multilingual Machine Translation,” in Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 2: Short Papers), Online only, 2022, p. 148–153.
[BibTeX] [Abstract] [Link]

Machine translation traditionally refers to translating from a single source language into a single target language. In recent years, the field has moved towards large neural models either translating from or into many languages. The model must be correctly cued to translate into the correct target language. This is typically done by prefixing language tokens onto the source or target sequence. The location and content of the prefix can vary and many use different approaches without much justification towards one approach or another. As a guidance to future researchers and directions for future work, we present a series of experiments that show how the positioning and type of a target language prefix token effects translation performance. We show that source side prefixes improve performance. Further, we find that the best language information to denote via tokens depends on the supported language set.

@inproceedings{wicks-duh-2022-effects,
title = "The Effects of Language Token Prefixing for Multilingual Machine Translation",
author = "Wicks, Rachel and
Duh, Kevin",
editor = "He, Yulan and
Ji, Heng and
Li, Sujian and
Liu, Yang and
Chang, Chua-Hui",
booktitle = "Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)",
month = nov,
year = "2022",
address = "Online only",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.aacl-short.19",
pages = "148--153",
abstract = "Machine translation traditionally refers to translating from a single source language into a single target language. In recent years, the field has moved towards large neural models either translating from or into many languages. The model must be correctly cued to translate into the correct target language. This is typically done by prefixing language tokens onto the source or target sequence. The location and content of the prefix can vary and many use different approaches without much justification towards one approach or another. As a guidance to future researchers and directions for future work, we present a series of experiments that show how the positioning and type of a target language prefix token effects translation performance. We show that source side prefixes improve performance. Further, we find that the best language information to denote via tokens depends on the supported language set.",
}

Sonal Joshi, Saurabh Kataria, Yiwen Shao, Piotr Żelasko, J. Villalba, S. Khudanpur, and N. Dehak, “Defense against Adversarial Attacks on Hybrid Speech Recognition System using Adversarial Fine-tuning with Denoiser,” in Interspeech, 2022.
[BibTeX] [Link]

@inproceedings{252346818,
title = {Defense against Adversarial Attacks on Hybrid Speech Recognition System using Adversarial Fine-tuning with Denoiser},
author = {{Sonal Joshi} and {Saurabh Kataria} and {Yiwen Shao} and {Piotr Żelasko} and {J. Villalba} and {S. Khudanpur} and {N. Dehak}},
year = 2022,
month = {9},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/b8c3c97f239a1048b460d659a14110cc7f7a499e},
}

J. Villalba, B. J. Borgstrom, Saurabh Kataria, Magdalena Rybicka, C. Castillo, Jaejin Cho, Leibny Paola García-Perera, P. Torres-Carrasquillo, and N. Dehak, “Advances in Cross-Lingual and Cross-Source Audio-Visual Speaker Recognition: The JHU-MIT System for NIST SRE21,” in The Speaker and Language Recognition Workshop, 2022.
[BibTeX] [Link]

@inproceedings{249827199,
title = {Advances in Cross-Lingual and Cross-Source Audio-Visual Speaker Recognition: The JHU-MIT System for NIST SRE21},
author = {{J. Villalba} and {B. J. Borgstrom} and {Saurabh Kataria} and {Magdalena Rybicka} and {C. Castillo} and {Jaejin Cho} and {Leibny Paola García-Perera} and {P. Torres-Carrasquillo} and {N. Dehak}},
year = 2022,
month = {6},
booktitle = {The Speaker and Language Recognition Workshop},
url = {https://www.semanticscholar.org/paper/9d9b5b782cbaf98bfb198b120c343d813c99ecf5},
}

Zach Wood-Doughty, Isabel Cachola, and Mark Dredze, “Proxy Model Explanations for Time Series RNNs,” in International Conference on Machine Learning and Applications, 2021.
[BibTeX] [Link]

@inproceedings{246291268,
title = {Proxy Model Explanations for Time Series RNNs},
author = {{Zach Wood-Doughty} and {Isabel Cachola} and {Mark Dredze}},
year = 2021,
month = {12},
booktitle = {International Conference on Machine Learning and Applications},
url = {https://www.semanticscholar.org/paper/9e031c15797f9e41598a6c7ebe583e3bb72dceb0},
}

M. Yarmohammadi, S. Wu, M. Marone, H. Xu, S. Ebner, G. Qin, Y. Chen, J. Guo, C. Harman, K. Murray, A. S. White, M. Dredze, and B. Van Durme, “Everything Is All It Takes: A Multipronged Strategy for Zero-Shot Cross-Lingual Information Extraction,” in Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Online and Punta Cana, Dominican Republic, 2021, p. 1950–1967. doi:10.18653/v1/2021.emnlp-main.149
[BibTeX] [Abstract] [Link]

Zero-shot cross-lingual information extraction (IE) describes the construction of an IE model for some target language, given existing annotations exclusively in some other language, typically English. While the advance of pretrained multilingual encoders suggests an easy optimism of {“}train on English, run on any language{”}, we find through a thorough exploration and extension of techniques that a combination of approaches, both new and old, leads to better performance than any one cross-lingual strategy in particular. We explore techniques including data projection and self-training, and how different pretrained encoders impact them. We use English-to-Arabic IE as our initial example, demonstrating strong performance in this setting for event extraction, named entity recognition, part-of-speech tagging, and dependency parsing. We then apply data projection and self-training to three tasks across eight target languages. Because no single set of techniques performs the best across all tasks, we encourage practitioners to explore various configurations of the techniques described in this work when seeking to improve on zero-shot training.

@inproceedings{yarmohammadi-etal-2021-everything,
title = "Everything Is All It Takes: A Multipronged Strategy for Zero-Shot Cross-Lingual Information Extraction",
author = "Yarmohammadi, Mahsa and
Wu, Shijie and
Marone, Marc and
Xu, Haoran and
Ebner, Seth and
Qin, Guanghui and
Chen, Yunmo and
Guo, Jialiang and
Harman, Craig and
Murray, Kenton and
White, Aaron Steven and
Dredze, Mark and
Van Durme, Benjamin",
editor = "Moens, Marie-Francine and
Huang, Xuanjing and
Specia, Lucia and
Yih, Scott Wen-tau",
booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing",
month = nov,
year = "2021",
address = "Online and Punta Cana, Dominican Republic",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.emnlp-main.149",
doi = "10.18653/v1/2021.emnlp-main.149",
pages = "1950--1967",
abstract = "Zero-shot cross-lingual information extraction (IE) describes the construction of an IE model for some target language, given existing annotations exclusively in some other language, typically English. While the advance of pretrained multilingual encoders suggests an easy optimism of {``}train on English, run on any language{''}, we find through a thorough exploration and extension of techniques that a combination of approaches, both new and old, leads to better performance than any one cross-lingual strategy in particular. We explore techniques including data projection and self-training, and how different pretrained encoders impact them. We use English-to-Arabic IE as our initial example, demonstrating strong performance in this setting for event extraction, named entity recognition, part-of-speech tagging, and dependency parsing. We then apply data projection and self-training to three tasks across eight target languages. Because no single set of techniques performs the best across all tasks, we encourage practitioners to explore various configurations of the techniques described in this work when seeking to improve on zero-shot training.",
}

A. Chinta, J. Zhang, A. DeLucia, M. Dredze, and A. L. Buczak, “Study of Manifestation of Civil Unrest on Twitter,” in Proceedings of the Seventh Workshop on Noisy User-generated Text (W-NUT 2021), Online, 2021, p. 396–409. doi:10.18653/v1/2021.wnut-1.44
[BibTeX] [Abstract] [Link]

Twitter is commonly used for civil unrest detection and forecasting tasks, but there is a lack of work in evaluating \textit{how} civil unrest manifests on Twitter across countries and events. We present two in-depth case studies for two specific large-scale events, one in a country with high (English) Twitter usage (Johannesburg riots in South Africa) and one in a country with low Twitter usage (Burayu massacre protests in Ethiopia). We show that while there is event signal during the events, there is little signal leading up to the events. In addition to the case studies, we train Ngram-based models on a larger set of Twitter civil unrest data across time, events, and countries and use machine learning explainability tools (SHAP) to identify important features. The models were able to find words indicative of civil unrest that generalized across countries. The 42 countries span Africa, Middle East, and Southeast Asia and the events range occur between 2014 and 2019.

@inproceedings{chinta-etal-2021-study,
title = "Study of Manifestation of Civil Unrest on {T}witter",
author = "Chinta, Abhinav and
Zhang, Jingyu and
DeLucia, Alexandra and
Dredze, Mark and
Buczak, Anna L.",
editor = "Xu, Wei and
Ritter, Alan and
Baldwin, Tim and
Rahimi, Afshin",
booktitle = "Proceedings of the Seventh Workshop on Noisy User-generated Text (W-NUT 2021)",
month = nov,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.wnut-1.44",
doi = "10.18653/v1/2021.wnut-1.44",
pages = "396--409",
abstract = "Twitter is commonly used for civil unrest detection and forecasting tasks, but there is a lack of work in evaluating \textit{how} civil unrest manifests on Twitter across countries and events. We present two in-depth case studies for two specific large-scale events, one in a country with high (English) Twitter usage (Johannesburg riots in South Africa) and one in a country with low Twitter usage (Burayu massacre protests in Ethiopia). We show that while there is event signal during the events, there is little signal leading up to the events. In addition to the case studies, we train Ngram-based models on a larger set of Twitter civil unrest data across time, events, and countries and use machine learning explainability tools (SHAP) to identify important features. The models were able to find words indicative of civil unrest that generalized across countries. The 42 countries span Africa, Middle East, and Southeast Asia and the events range occur between 2014 and 2019.",
}

A. Buczak, Benjamin D. Baugher, Christine S. Martin, Meg W. Keiley-Listermann, J. Howard, Nathan H. Parrish, Anton Q. Stalick, D. S. Berman, and Mark Dredze, “Crystal Cube: Forecasting Disruptive Events,” in Applied Artificial Intelligence, 2021.
[BibTeX] [Link]

@inproceedings{244096848,
title = {Crystal Cube: Forecasting Disruptive Events},
author = {{A. Buczak} and {Benjamin D. Baugher} and {Christine S. Martin} and {Meg W. Keiley-Listermann} and {J. Howard} and {Nathan H. Parrish} and {Anton Q. Stalick} and {D. S. Berman} and {Mark Dredze}},
year = 2021,
month = {11},
booktitle = {Applied Artificial Intelligence},
url = {https://www.semanticscholar.org/paper/3168dec5c6a5c1441f258c14d05f8520f20ecbaf},
}

M. A. Gordon, K. Duh, and J. Kaplan, “Data and Parameter Scaling Laws for Neural Machine Translation,” in Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Online and Punta Cana, Dominican Republic, 2021, p. 5915–5922. doi:10.18653/v1/2021.emnlp-main.478
[BibTeX] [Abstract] [Link]

We observe that the development cross-entropy loss of supervised neural machine translation models scales like a power law with the amount of training data and the number of non-embedding parameters in the model. We discuss some practical implications of these results, such as predicting BLEU achieved by large scale models and predicting the ROI of labeling data in low-resource language pairs.

@inproceedings{gordon-etal-2021-data,
title = "Data and Parameter Scaling Laws for Neural Machine Translation",
author = "Gordon, Mitchell A and
Duh, Kevin and
Kaplan, Jared",
editor = "Moens, Marie-Francine and
Huang, Xuanjing and
Specia, Lucia and
Yih, Scott Wen-tau",
booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing",
month = nov,
year = "2021",
address = "Online and Punta Cana, Dominican Republic",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.emnlp-main.478",
doi = "10.18653/v1/2021.emnlp-main.478",
pages = "5915--5922",
abstract = "We observe that the development cross-entropy loss of supervised neural machine translation models scales like a power law with the amount of training data and the number of non-embedding parameters in the model. We discuss some practical implications of these results, such as predicting BLEU achieved by large scale models and predicting the ROI of labeling data in low-resource language pairs.",
}

T. Vieira, R. Cotterell, and J. Eisner, “Searching for More Efficient Dynamic Programs,” in Findings of EMNLP’21, Punta Cana, 2021, p. 3812–3830. doi:10.18653/v1/2021.findings-emnlp.322
[BibTeX] [Link]

@InProceedings{vieira-et-al-2021-emnlp,
aclid = "2021.findings-emnlp.322",
doi = "10.18653/v1/2021.findings-emnlp.322",
author = "Tim Vieira and Ryan Cotterell and Jason Eisner",
title = "Searching for More Efficient Dynamic Programs",
booktitle = "Findings of EMNLP'21",
pages = "3812--3830",
year = "2021",
month = nov,
address = "Punta Cana",
URL = "http://cs.jhu.edu/~jason/papers/#vieira-et-al-2021-emnlp",
}

R. Shin, C. H. Lin, S. Thomson, C. Chen, S. Roy, E. Antonios Platanios, A. Pauls, D. Klein, J. Eisner, and B. V. Durme, “Constrained Language Models Yield Few-Shot Semantic Parsers,” in Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Punta Cana, 2021, p. 7699–7715. doi:10.18653/v1/2021.emnlp-main.608
[BibTeX] [Link]

@InProceedings{semanticmachines-2021-emnlp,
aclid = "2021.emnlp-main.608",
doi = "10.18653/v1/2021.emnlp-main.608",
author = "Richard Shin and Christopher H. Lin and Sam Thomson
and Charles Chen and Subhro Roy and Emmanouil Antonios
Platanios and Adam Pauls and Dan Klein and Jason Eisner
and Benjamin Van Durme",
title = "Constrained Language Models Yield Few-Shot Semantic
Parsers",
booktitle = "Proceedings of the 2021 Conference on Empirical
Methods in Natural Language Processing",
pages = "7699--7715",
year = "2021",
month = nov,
address = "Punta Cana",
URL = "http://cs.jhu.edu/~jason/papers/#semanticmachines-2021-emnlp",
}

Joseph P. Robinson, Can Qin, Ming Shao, Matthew A. Turk, R. Chellappa, and Y. Fu, “The 5th Recognizing Families in the Wild Data Challenge: Predicting Kinship from Faces,” in IEEE International Conference on Automatic Face & Gesture Recognition, 2021.
[BibTeX] [Link]

@inproceedings{244728315,
title = {The 5th Recognizing Families in the Wild Data Challenge: Predicting Kinship from Faces},
author = {{Joseph P. Robinson} and {Can Qin} and {Ming Shao} and {Matthew A. Turk} and {R. Chellappa} and {Y. Fu}},
year = 2021,
month = {10},
booktitle = {IEEE International Conference on Automatic Face & Gesture Recognition},
url = {https://www.semanticscholar.org/paper/9f260bdd4030af5297a9c1cbb817c75701ac8c83},
}

M. Sophocleous, J. Georgiou, A. Andreou, Yosi Shacham-Diamand, Theerawit Wilaiprasitporn, J. Atkinson, Paddy J. French, E. García-Breijo, and Mohammad Russel, “Guest Editorial Special Issue on Sensors Tutorials: A Vigorous Dive Into the Vast Sea of Sensor- Related Knowledge—Part I,” in IEEE Sensors Journal, 2021.
[BibTeX] [Link]

@inproceedings{245002248,
title = {Guest Editorial Special Issue on Sensors Tutorials: A Vigorous Dive Into the Vast Sea of Sensor- Related Knowledge—Part I},
author = {{M. Sophocleous} and {J. Georgiou} and {A. Andreou} and {Yosi Shacham-Diamand} and {Theerawit Wilaiprasitporn} and {J. Atkinson} and {Paddy J. French} and {E. García-Breijo} and {Mohammad Russel}},
year = 2021,
month = {10},
booktitle = {IEEE Sensors Journal},
url = {https://www.semanticscholar.org/paper/72e190cfe76cde934943ae35908bff346d4c970d},
}

Hossein Souri, Pirazh Khorramshahi, Chun Pong Lau, Micah Goldblum, and R. Chellappa, “Identification of Attack-Specific Signatures in Adversarial Examples,” in arXiv.org, 2021.
[BibTeX] [Link]

@inproceedings{238743967,
title = {Identification of Attack-Specific Signatures in Adversarial Examples},
author = {{Hossein Souri} and {Pirazh Khorramshahi} and {Chun Pong Lau} and {Micah Goldblum} and {R. Chellappa}},
year = 2021,
month = {10},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/7cfeca9f831e4f2d31114215abaa5078a98d1656},
}

Saurabhchand Bhati, J. Villalba, Piotr Żelasko, L. Moro-Velázquez, and N. Dehak, “Unsupervised Speech Segmentation and Variable Rate Representation Learning Using Segmental Contrastive Predictive Coding,” in IEEE/ACM Transactions on Audio Speech and Language Processing, 2021.
[BibTeX] [Link]

@inproceedings{238408084,
title = {Unsupervised Speech Segmentation and Variable Rate Representation Learning Using Segmental Contrastive Predictive Coding},
author = {{Saurabhchand Bhati} and {J. Villalba} and {Piotr Żelasko} and {L. Moro-Velázquez} and {N. Dehak}},
year = 2021,
month = {10},
booktitle = {IEEE/ACM Transactions on Audio Speech and Language Processing},
url = {https://www.semanticscholar.org/paper/3c2502b6d82ba4fca35fb871e7ed697fb4952f23},
}

W. Wu, K. Duh, and D. Yarowsky, “Sequence Models for Computational Etymology of Borrowings,” in Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, Online, 2021, p. 4032–4037. doi:10.18653/v1/2021.findings-acl.353
[BibTeX] [Link]

@inproceedings{wu-etal-2021-sequence,
title = "Sequence Models for Computational Etymology of Borrowings",
author = "Wu, Winston and
Duh, Kevin and
Yarowsky, David",
editor = "Zong, Chengqing and
Xia, Fei and
Li, Wenjie and
Navigli, Roberto",
booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.findings-acl.353",
doi = "10.18653/v1/2021.findings-acl.353",
pages = "4032--4037",
}

L. Zhou, L. Ding, K. Duh, S. Watanabe, R. Sasano, and K. Takeda, “Self-Guided Curriculum Learning for Neural Machine Translation,” in Proceedings of the 18th International Conference on Spoken Language Translation (IWSLT 2021), Bangkok, Thailand (online), 2021, p. 206–214. doi:10.18653/v1/2021.iwslt-1.25
[BibTeX] [Abstract] [Link]

In supervised learning, a well-trained model should be able to recover ground truth accurately, i.e. the predicted labels are expected to resemble the ground truth labels as much as possible. Inspired by this, we formulate a difficulty criterion based on the recovery degrees of training examples. Motivated by the intuition that after skimming through the training corpus, the neural machine translation (NMT) model {“}knows{”} how to schedule a suitable curriculum according to learning difficulty, we propose a self-guided curriculum learning strategy that encourages the NMT model to learn from easy to hard on the basis of recovery degrees. Specifically, we adopt sentence-level BLEU score as the proxy of recovery degree. Experimental results on translation benchmarks including WMT14 English-German and WMT17 Chinese-English demonstrate that our proposed method considerably improves the recovery degree, thus consistently improving the translation performance.

@inproceedings{zhou-etal-2021-self,
title = "Self-Guided Curriculum Learning for Neural Machine Translation",
author = "Zhou, Lei and
Ding, Liang and
Duh, Kevin and
Watanabe, Shinji and
Sasano, Ryohei and
Takeda, Koichi",
editor = "Federico, Marcello and
Waibel, Alex and
Costa-juss{\`a}, Marta R. and
Niehues, Jan and
Stuker, Sebastian and
Salesky, Elizabeth",
booktitle = "Proceedings of the 18th International Conference on Spoken Language Translation (IWSLT 2021)",
month = aug,
year = "2021",
address = "Bangkok, Thailand (online)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.iwslt-1.25",
doi = "10.18653/v1/2021.iwslt-1.25",
pages = "206--214",
abstract = "In supervised learning, a well-trained model should be able to recover ground truth accurately, i.e. the predicted labels are expected to resemble the ground truth labels as much as possible. Inspired by this, we formulate a difficulty criterion based on the recovery degrees of training examples. Motivated by the intuition that after skimming through the training corpus, the neural machine translation (NMT) model {``}knows{''} how to schedule a suitable curriculum according to learning difficulty, we propose a self-guided curriculum learning strategy that encourages the NMT model to learn from easy to hard on the basis of recovery degrees. Specifically, we adopt sentence-level BLEU score as the proxy of recovery degree. Experimental results on translation benchmarks including WMT14 English-German and WMT17 Chinese-English demonstrate that our proposed method considerably improves the recovery degree, thus consistently improving the translation performance.",
}

X. Zhang and K. Duh, “Approaching Sign Language Gloss Translation as a Low-Resource Machine Translation Task,” in Proceedings of the 1st International Workshop on Automatic Translation for Signed and Spoken Languages (AT4SSL), Virtual, 2021, p. 60–70.
[BibTeX] [Abstract] [Link]

A cascaded Sign Language Translation system first maps sign videos to gloss annotations and then translates glosses into a spoken languages. This work focuses on the second-stage gloss translation component, which is challenging due to the scarcity of publicly available parallel data. We approach gloss translation as a low-resource machine translation task and investigate two popular methods for improving translation quality: hyperparameter search and backtranslation. We discuss the potentials and pitfalls of these methods based on experiments on the RWTH-PHOENIX-Weather 2014T dataset.

@inproceedings{zhang-duh-2021-approaching,
title = "Approaching Sign Language Gloss Translation as a Low-Resource Machine Translation Task",
author = "Zhang, Xuan and
Duh, Kevin",
editor = "Shterionov, Dimitar",
booktitle = "Proceedings of the 1st International Workshop on Automatic Translation for Signed and Spoken Languages (AT4SSL)",
month = aug,
year = "2021",
address = "Virtual",
publisher = "Association for Machine Translation in the Americas",
url = "https://aclanthology.org/2021.mtsummit-at4ssl.7",
pages = "60--70",
abstract = "A cascaded Sign Language Translation system first maps sign videos to gloss annotations and then translates glosses into a spoken languages. This work focuses on the second-stage gloss translation component, which is challenging due to the scarcity of publicly available parallel data. We approach gloss translation as a low-resource machine translation task and investigate two popular methods for improving translation quality: hyperparameter search and backtranslation. We discuss the potentials and pitfalls of these methods based on experiments on the RWTH-PHOENIX-Weather 2014T dataset.",
}

E. Schumacher, J. Mayfield, and M. Dredze, “Cross-Lingual Transfer in Zero-Shot Cross-Language Entity Linking,” in Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, Online, 2021, p. 583–595. doi:10.18653/v1/2021.findings-acl.52
[BibTeX] [Link]

@inproceedings{schumacher-etal-2021-cross,
title = "Cross-Lingual Transfer in Zero-Shot Cross-Language Entity Linking",
author = "Schumacher, Elliot and
Mayfield, James and
Dredze, Mark",
editor = "Zong, Chengqing and
Xia, Fei and
Li, Wenjie and
Navigli, Roberto",
booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.findings-acl.52",
doi = "10.18653/v1/2021.findings-acl.52",
pages = "583--595",
}

K. Harrigian, C. Aguirre, and M. Dredze, “On the State of Social Media Data for Mental Health Research,” in Proceedings of the Seventh Workshop on Computational Linguistics and Clinical Psychology: Improving Access, Online, 2021, p. 15–24. doi:10.18653/v1/2021.clpsych-1.2
[BibTeX] [Abstract] [Link]

Data-driven methods for mental health treatment and surveillance have become a major focus in computational science research in the last decade. However, progress in the domain remains bounded by the availability of adequate data. Prior systematic reviews have not necessarily made it possible to measure the degree to which data-related challenges have affected research progress. In this paper, we offer an analysis specifically on the state of social media data that exists for conducting mental health research. We do so by introducing an open-source directory of mental health datasets, annotated using a standardized schema to facilitate meta-analysis.

@inproceedings{harrigian-etal-2021-state,
title = "On the State of Social Media Data for Mental Health Research",
author = "Harrigian, Keith and
Aguirre, Carlos and
Dredze, Mark",
editor = "Goharian, Nazli and
Resnik, Philip and
Yates, Andrew and
Ireland, Molly and
Niederhoffer, Kate and
Resnik, Rebecca",
booktitle = "Proceedings of the Seventh Workshop on Computational Linguistics and Clinical Psychology: Improving Access",
month = jun,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.clpsych-1.2",
doi = "10.18653/v1/2021.clpsych-1.2",
pages = "15--24",
abstract = "Data-driven methods for mental health treatment and surveillance have become a major focus in computational science research in the last decade. However, progress in the domain remains bounded by the availability of adequate data. Prior systematic reviews have not necessarily made it possible to measure the degree to which data-related challenges have affected research progress. In this paper, we offer an analysis specifically on the state of social media data that exists for conducting mental health research. We do so by introducing an open-source directory of mental health datasets, annotated using a standardized schema to facilitate meta-analysis.",
}

Z. Wood-Doughty, P. Xu, X. Liu, and M. Dredze, “Using Noisy Self-Reports to Predict Twitter User Demographics,” in Proceedings of the Ninth International Workshop on Natural Language Processing for Social Media, Online, 2021, p. 123–137. doi:10.18653/v1/2021.socialnlp-1.11
[BibTeX] [Abstract] [Link]

Computational social science studies often contextualize content analysis within standard demographics. Since demographics are unavailable on many social media platforms (e.g. Twitter), numerous studies have inferred demographics automatically. Despite many studies presenting proof-of-concept inference of race and ethnicity, training of practical systems remains elusive since there are few annotated datasets. Existing datasets are small, inaccurate, or fail to cover the four most common racial and ethnic groups in the United States. We present a method to identify self-reports of race and ethnicity from Twitter profile descriptions. Despite the noise of automated supervision, our self-report datasets enable improvements in classification performance on gold standard self-report survey data. The result is a reproducible method for creating large-scale training resources for race and ethnicity.

@inproceedings{wood-doughty-etal-2021-using,
title = "Using Noisy Self-Reports to Predict {T}witter User Demographics",
author = "Wood-Doughty, Zach and
Xu, Paiheng and
Liu, Xiao and
Dredze, Mark",
editor = "Ku, Lun-Wei and
Li, Cheng-Te",
booktitle = "Proceedings of the Ninth International Workshop on Natural Language Processing for Social Media",
month = jun,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.socialnlp-1.11",
doi = "10.18653/v1/2021.socialnlp-1.11",
pages = "123--137",
abstract = "Computational social science studies often contextualize content analysis within standard demographics. Since demographics are unavailable on many social media platforms (e.g. Twitter), numerous studies have inferred demographics automatically. Despite many studies presenting proof-of-concept inference of race and ethnicity, training of practical systems remains elusive since there are few annotated datasets. Existing datasets are small, inaccurate, or fail to cover the four most common racial and ethnic groups in the United States. We present a method to identify self-reports of race and ethnicity from Twitter profile descriptions. Despite the noise of automated supervision, our self-report datasets enable improvements in classification performance on gold standard self-report survey data. The result is a reproducible method for creating large-scale training resources for race and ethnicity.",
}

C. Lin, A. Jaech, X. Li, Matt Gormley, and J. Eisner, “Limitations of Autoregressive Models and Their Alternatives,” in Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT), Online, 2021, p. 5147–5173. doi:10.18653/v1/2021.naacl-main.405
[BibTeX] [Link]

@InProceedings{lin-et-al-2021-naacl,
aclid = "2021.naacl-main.405",
doi = "10.18653/v1/2021.naacl-main.405",
author = "Chu-Cheng Lin and Aaron Jaech and Xin Li and Matt
Gormley and Jason Eisner",
title = "Limitations of Autoregressive Models and Their
Alternatives",
booktitle = "Proceedings of the 2021 Conference of the North
American Chapter of the Association for Computational
Linguistics: Human Language Technologies (NAACL-HLT)",
pages = "5147--5173",
year = "2021",
month = jun,
address = "Online",
URL = "http://cs.jhu.edu/~jason/papers/#lin-et-al-2021-naacl",
}

G. Qin and J. Eisner, “Learning How To Ask: Querying LMs with Mixtures of Soft Prompts,” in Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT), Online, 2021, p. 5203–5212. doi:10.18653/v1/2021.naacl-main.410
[BibTeX] [Link]

@InProceedings{qin-eisner-2021,
aclid = "2021.naacl-main.410",
doi = "10.18653/v1/2021.naacl-main.410",
author = "Guanghui Qin and Jason Eisner",
title = "Learning How To Ask: Querying {LM}s with Mixtures of
Soft Prompts",
booktitle = "Proceedings of the 2021 Conference of the North
American Chapter of the Association for Computational
Linguistics: Human Language Technologies (NAACL-HLT)",
pages = "5203--5212",
year = "2021",
month = jun,
address = "Online",
note = "Best Short Paper Award.",
URL = "http://cs.jhu.edu/~jason/papers/#qin-eisner-2021",
}

J. Shi, J. D. Amith, R. Castillo Garc{‘i}a, E. Guadalupe Sierra, K. Duh, and S. Watanabe, “Leveraging End-to-End ASR for Endangered Language Documentation: An Empirical Study on Yolóxochitl Mixtec,” in Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, Online, 2021, p. 1134–1145. doi:10.18653/v1/2021.eacl-main.96
[BibTeX] [Abstract] [Link]

{“}Transcription bottlenecks{”}, created by a shortage of effective human transcribers (i.e., transcriber shortage), are one of the main challenges to endangered language (EL) documentation. Automatic speech recognition (ASR) has been suggested as a tool to overcome such bottlenecks. Following this suggestion, we investigated the effectiveness for EL documentation of end-to-end ASR, which unlike Hidden Markov Model ASR systems, eschews linguistic resources but is instead more dependent on large-data settings. We open source a Yoloxóchitl Mixtec EL corpus. First, we review our method in building an end-to-end ASR system in a way that would be reproducible by the ASR community. We then propose a novice transcription correction task and demonstrate how ASR systems and novice transcribers can work together to improve EL documentation. We believe this combinatory methodology would mitigate the transcription bottleneck and transcriber shortage that hinders EL documentation.

@inproceedings{shi-etal-2021-leveraging,
title = "Leveraging End-to-End {ASR} for Endangered Language Documentation: An Empirical Study on Yol{\'o}xochitl {M}ixtec",
author = "Shi, Jiatong and
Amith, Jonathan D. and
Castillo Garc{\'\i}a, Rey and
Guadalupe Sierra, Esteban and
Duh, Kevin and
Watanabe, Shinji",
editor = "Merlo, Paola and
Tiedemann, Jorg and
Tsarfaty, Reut",
booktitle = "Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume",
month = apr,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.eacl-main.96",
doi = "10.18653/v1/2021.eacl-main.96",
pages = "1134--1145",
abstract = "{``}Transcription bottlenecks{''}, created by a shortage of effective human transcribers (i.e., transcriber shortage), are one of the main challenges to endangered language (EL) documentation. Automatic speech recognition (ASR) has been suggested as a tool to overcome such bottlenecks. Following this suggestion, we investigated the effectiveness for EL documentation of end-to-end ASR, which unlike Hidden Markov Model ASR systems, eschews linguistic resources but is instead more dependent on large-data settings. We open source a Yolox{\'o}chitl Mixtec EL corpus. First, we review our method in building an end-to-end ASR system in a way that would be reproducible by the ASR community. We then propose a novice transcription correction task and demonstrate how ASR systems and novice transcribers can work together to improve EL documentation. We believe this combinatory methodology would mitigate the transcription bottleneck and transcriber shortage that hinders EL documentation.",
}

X. Huang, M. J. Paul, F. Dernoncourt, R. Burke, and M. Dredze, “User Factor Adaptation for User Embedding via Multitask Learning,” in Proceedings of the Second Workshop on Domain Adaptation for NLP, Kyiv, Ukraine, 2021, p. 172–182.
[BibTeX] [Abstract] [Link]

Language varies across users and their interested fields in social media data: words authored by a user across his/her interests may have different meanings (e.g., cool) or sentiments (e.g., fast). However, most of the existing methods to train user embeddings ignore the variations across user interests, such as product and movie categories (e.g., drama vs. action). In this study, we treat the user interest as domains and empirically examine how the user language can vary across the user factor in three English social media datasets. We then propose a user embedding model to account for the language variability of user interests via a multitask learning framework. The model learns user language and its variations without human supervision. While existing work mainly evaluated the user embedding by extrinsic tasks, we propose an intrinsic evaluation via clustering and evaluate user embeddings by an extrinsic task, text classification. The experiments on the three English-language social media datasets show that our proposed approach can generally outperform baselines via adapting the user factor.

@inproceedings{huang-etal-2021-user,
title = "User Factor Adaptation for User Embedding via Multitask Learning",
author = "Huang, Xiaolei and
Paul, Michael J. and
Dernoncourt, Franck and
Burke, Robin and
Dredze, Mark",
editor = "Ben-David, Eyal and
Cohen, Shay and
McDonald, Ryan and
Plank, Barbara and
Reichart, Roi and
Rotman, Guy and
Ziser, Yftah",
booktitle = "Proceedings of the Second Workshop on Domain Adaptation for NLP",
month = apr,
year = "2021",
address = "Kyiv, Ukraine",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.adaptnlp-1.18",
pages = "172--182",
abstract = "Language varies across users and their interested fields in social media data: words authored by a user across his/her interests may have different meanings (e.g., cool) or sentiments (e.g., fast). However, most of the existing methods to train user embeddings ignore the variations across user interests, such as product and movie categories (e.g., drama vs. action). In this study, we treat the user interest as domains and empirically examine how the user language can vary across the user factor in three English social media datasets. We then propose a user embedding model to account for the language variability of user interests via a multitask learning framework. The model learns user language and its variations without human supervision. While existing work mainly evaluated the user embedding by extrinsic tasks, we propose an intrinsic evaluation via clustering and evaluate user embeddings by an extrinsic task, text classification. The experiments on the three English-language social media datasets show that our proposed approach can generally outperform baselines via adapting the user factor.",
}

M. Martindale, K. Duh, and M. Carpuat, “Machine Translation Believability,” in Proceedings of the First Workshop on Bridging Human–Computer Interaction and Natural Language Processing, Online, 2021, p. 88–95.
[BibTeX] [Abstract] [Link]

Successful Machine Translation (MT) deployment requires understanding not only the intrinsic qualities of MT output, such as fluency and adequacy, but also user perceptions. Users who do not understand the source language respond to MT output based on their perception of the likelihood that the meaning of the MT output matches the meaning of the source text. We refer to this as believability. Output that is not believable may be off-putting to users, but believable MT output with incorrect meaning may mislead them. In this work, we study the relationship of believability to fluency and adequacy by applying traditional MT direct assessment protocols to annotate all three features on the output of neural MT systems. Quantitative analysis of these annotations shows that believability is closely related to but distinct from fluency, and initial qualitative analysis suggests that semantic features may account for the difference.

@inproceedings{martindale-etal-2021-machine,
title = "Machine Translation Believability",
author = "Martindale, Marianna and
Duh, Kevin and
Carpuat, Marine",
editor = "Blodgett, Su Lin and
Madaio, Michael and
O'Connor, Brendan and
Wallach, Hanna and
Yang, Qian",
booktitle = "Proceedings of the First Workshop on Bridging Human{--}Computer Interaction and Natural Language Processing",
month = apr,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.hcinlp-1.14",
pages = "88--95",
abstract = "Successful Machine Translation (MT) deployment requires understanding not only the intrinsic qualities of MT output, such as fluency and adequacy, but also user perceptions. Users who do not understand the source language respond to MT output based on their perception of the likelihood that the meaning of the MT output matches the meaning of the source text. We refer to this as believability. Output that is not believable may be off-putting to users, but believable MT output with incorrect meaning may mislead them. In this work, we study the relationship of believability to fluency and adequacy by applying traditional MT direct assessment protocols to annotate all three features on the output of neural MT systems. Quantitative analysis of these annotations shows that believability is closely related to but distinct from fluency, and initial qualitative analysis suggests that semantic features may account for the difference.",
}

A. Hussein, Shammur A. Chowdhury, N. Dehak, and Ahmed Ali, “Balanced End-to-End Monolingual pre-training for Low-Resourced Indic Languages Code-Switching Speech Recognition.” 2021.
[BibTeX] [Link]

@inproceedings{246863876,
title = {Balanced End-to-End Monolingual pre-training for Low-Resourced Indic Languages Code-Switching Speech Recognition},
author = {{A. Hussein} and {Shammur A. Chowdhury} and {N. Dehak} and {Ahmed Ali}},
year = 2021,
month = {6},
booktitle = {},
url = {https://www.semanticscholar.org/paper/4781f897c02809c1522a06668ae1f4fa0e68e5ac},
}

Prithviraj Dhar, Joshua Gleason, A. Roy, C. Castillo, and R. Chellappa, “PASS: Protected Attribute Suppression System for Mitigating Bias in Face Recognition,” in IEEE International Conference on Computer Vision, 2021.
[BibTeX] [Link]

@inproceedings{236956411,
title = {PASS: Protected Attribute Suppression System for Mitigating Bias in Face Recognition},
author = {{Prithviraj Dhar} and {Joshua Gleason} and {A. Roy} and {C. Castillo} and {R. Chellappa}},
year = 2021,
month = {8},
booktitle = {IEEE International Conference on Computer Vision},
url = {https://www.semanticscholar.org/paper/5451ff6ea2e7bb3d40bb61889bb3494cf0eebb3e},
}

S. Sia and K. Duh, “Adaptive Mixed Component LDA for Low Resource Topic Modeling,” in Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, Online, 2021, p. 2451–2469. doi:10.18653/v1/2021.eacl-main.209
[BibTeX] [Abstract] [Link]

Probabilistic topic models in low data resource scenarios are faced with less reliable estimates due to sparsity of discrete word co-occurrence counts, and do not have the luxury of retraining word or topic embeddings using neural methods. In this challenging resource constrained setting, we explore mixture models which interpolate between the discrete and continuous topic-word distributions that utilise pre-trained embeddings to improve topic coherence. We introduce an automatic trade-off between the discrete and continuous representations via an adaptive mixture coefficient, which places greater weight on the discrete representation when the corpus statistics are more reliable. The adaptive mixture coefficient takes into account global corpus statistics, and the uncertainty in each topic{‘}s continuous distributions. Our approach outperforms the fully discrete, fully continuous, and static mixture model on topic coherence in low resource settings. We additionally demonstrate the generalisability of our method by extending it to handle multilingual document collections.

@inproceedings{sia-duh-2021-adaptive,
title = "Adaptive Mixed Component {LDA} for Low Resource Topic Modeling",
author = "Sia, Suzanna and
Duh, Kevin",
editor = "Merlo, Paola and
Tiedemann, Jorg and
Tsarfaty, Reut",
booktitle = "Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume",
month = apr,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.eacl-main.209",
doi = "10.18653/v1/2021.eacl-main.209",
pages = "2451--2469",
abstract = "Probabilistic topic models in low data resource scenarios are faced with less reliable estimates due to sparsity of discrete word co-occurrence counts, and do not have the luxury of retraining word or topic embeddings using neural methods. In this challenging resource constrained setting, we explore mixture models which interpolate between the discrete and continuous topic-word distributions that utilise pre-trained embeddings to improve topic coherence. We introduce an automatic trade-off between the discrete and continuous representations via an adaptive mixture coefficient, which places greater weight on the discrete representation when the corpus statistics are more reliable. The adaptive mixture coefficient takes into account global corpus statistics, and the uncertainty in each topic{'}s continuous distributions. Our approach outperforms the fully discrete, fully continuous, and static mixture model on topic coherence in low resource settings. We additionally demonstrate the generalisability of our method by extending it to handle multilingual document collections.",
}

Jonah P. Sengupta, M. Villemur, and A. Andreou, “Efficient, event-driven feature extraction and unsupervised object tracking for embedded applications,” in Annual Conference on Information Sciences and Systems, 2021.
[BibTeX] [Link]

@inproceedings{233333562,
title = {Efficient, event-driven feature extraction and unsupervised object tracking for embedded applications},
author = {{Jonah P. Sengupta} and {M. Villemur} and {A. Andreou}},
year = 2021,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/b943079dc74c91a11ff4c7ccd9477775398edba2},
}

R. Pappagari, Piotr Żelasko, Agnieszka Mikołajczyk, Piotr Pęzik, and N. Dehak, “Joint Prediction of Truecasing and Punctuation for Conversational Speech in Low-Resource Scenarios,” in Automatic Speech Recognition & Understanding, 2021.
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@inproceedings{237491841,
title = {Joint Prediction of Truecasing and Punctuation for Conversational Speech in Low-Resource Scenarios},
author = {{R. Pappagari} and {Piotr Żelasko} and {Agnieszka Mikołajczyk} and {Piotr Pęzik} and {N. Dehak}},
year = 2021,
month = {9},
booktitle = {Automatic Speech Recognition & Understanding},
url = {https://www.semanticscholar.org/paper/cad80d9a6ba7c943da74be90c7d3302a2f463099},
}

Aviad Shtrosberg, J. Villalba, N. Dehak, Azaria Cohen, and Bar Ben-Yair, “Invariant Representation Learning for Robust Far-Field Speaker Recognition,” in International Conference on Statistical Language and Speech Processing, 2021.
[BibTeX] [Link]

@inproceedings{239039731,
title = {Invariant Representation Learning for Robust Far-Field Speaker Recognition},
author = {{Aviad Shtrosberg} and {J. Villalba} and {N. Dehak} and {Azaria Cohen} and {Bar Ben-Yair}},
year = 2021,
booktitle = {International Conference on Statistical Language and Speech Processing},
url = {https://www.semanticscholar.org/paper/f157b429553c4a6165856783ec879cd8d0f6a4cd},
}

Kelly Marchisio, Youngser Park, Ali Saad-Eldin, A. Alyakin, Kevin Duh, C. Priebe, and Philipp Koehn, “An Analysis of Euclidean vs. Graph-Based Framing for Bilingual Lexicon Induction from Word Embedding Spaces,” in Conference on Empirical Methods in Natural Language Processing, 2021.
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@inproceedings{237941142,
title = {An Analysis of Euclidean vs. Graph-Based Framing for Bilingual Lexicon Induction from Word Embedding Spaces},
author = {{Kelly Marchisio} and {Youngser Park} and {Ali Saad-Eldin} and {A. Alyakin} and {Kevin Duh} and {C. Priebe} and {Philipp Koehn}},
year = 2021,
month = {9},
booktitle = {Conference on Empirical Methods in Natural Language Processing},
url = {https://www.semanticscholar.org/paper/0a5fc6d1735dd2761fc31fad5a3b40a4fa06546b},
}

Magdalena Rybicka, J. Villalba, Piotr Żelasko, N. Dehak, and K. Kowalczyk, “Spine2Net: SpineNet with Res2Net and Time-Squeeze-and-Excitation Blocks for Speaker Recognition,” in Interspeech, 2021.
[BibTeX] [Link]

@inproceedings{239671591,
title = {Spine2Net: SpineNet with Res2Net and Time-Squeeze-and-Excitation Blocks for Speaker Recognition},
author = {{Magdalena Rybicka} and {J. Villalba} and {Piotr Żelasko} and {N. Dehak} and {K. Kowalczyk}},
year = 2021,
month = {8},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/62a007787bdf51bb58668d2a88df18850c4e9e28},
}

Saurabh Kataria, J. Villalba, Piotr Żelasko, Laureano Moro-Vel’azquez, and N. Dehak, “Deep Feature CycleGANs: Speaker Identity Preserving Non-Parallel Microphone-Telephone Domain Adaptation for Speaker Verification,” in Interspeech, 2021.
[BibTeX] [Link]

@inproceedings{233024923,
title = {Deep Feature CycleGANs: Speaker Identity Preserving Non-Parallel Microphone-Telephone Domain Adaptation for Speaker Verification},
author = {{Saurabh Kataria} and {J. Villalba} and {Piotr Żelasko} and {Laureano Moro-Vel'azquez} and {N. Dehak}},
year = 2021,
month = {4},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/c3bb7ff3eba44535c9b704ee52041f91bde7bcd0},
}

L. Moro-Velázquez, J. Gómez-García, N. Dehak, and Juan Ignacio Godino-Llorente, “New tools for the differential evaluation of Parkinson’s disease using voice and speech processing,” in IberSPEECH Conference, 2021.
[BibTeX] [Link]

@inproceedings{232285765,
title = {New tools for the differential evaluation of Parkinson's disease using voice and speech processing},
author = {{L. Moro-Velázquez} and {J. Gómez-García} and {N. Dehak} and {Juan Ignacio Godino-Llorente}},
year = 2021,
month = {3},
booktitle = {IberSPEECH Conference},
url = {https://www.semanticscholar.org/paper/c76e00b4e7c3fa5774cb61a194535086f53b7802},
}

Neehar Peri, Joshua Gleason, C. Castillo, T. Bourlai, Vishal M. Patel, and R. Chellappa, “A Synthesis-Based Approach for Thermal-to-Visible Face Verification,” in IEEE International Conference on Automatic Face & Gesture Recognition, 2021.
[BibTeX] [Link]

@inproceedings{237266437,
title = {A Synthesis-Based Approach for Thermal-to-Visible Face Verification},
author = {{Neehar Peri} and {Joshua Gleason} and {C. Castillo} and {T. Bourlai} and {Vishal M. Patel} and {R. Chellappa}},
year = 2021,
month = {8},
booktitle = {IEEE International Conference on Automatic Face & Gesture Recognition},
url = {https://www.semanticscholar.org/paper/edcfc2e222d08c51a9f1087fb29252b659d9b071},
}

Jonah P. Sengupta, M. Villemur, Daniel R. Mendat, Gaspar Tognetti, and A. Andreou, “Architecture and Algorithm Co-Design Framework for Embedded Processors in Event-Based Cameras,” in International Symposium on Circuits and Systems, 2021.
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@inproceedings{235520107,
title = {Architecture and Algorithm Co-Design Framework for Embedded Processors in Event-Based Cameras},
author = {{Jonah P. Sengupta} and {M. Villemur} and {Daniel R. Mendat} and {Gaspar Tognetti} and {A. Andreou}},
year = 2021,
month = {5},
booktitle = {International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/c7bc38e1a275d8e17aa779f0d66c567398c5d0cb},
}

Saurabhchand Bhati, J. Villalba, Piotr Żelasko, L. Moro-Velázquez, and N. Dehak, “Segmental Contrastive Predictive Coding for Unsupervised Word Segmentation,” in Interspeech, 2021.
[BibTeX] [Link]

@inproceedings{235352541,
title = {Segmental Contrastive Predictive Coding for Unsupervised Word Segmentation},
author = {{Saurabhchand Bhati} and {J. Villalba} and {Piotr Żelasko} and {L. Moro-Velázquez} and {N. Dehak}},
year = 2021,
month = {6},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/642dab29e680f516eb25949d616a24e0ad147a19},
}

Navaneeth Bodla, G. Shrivastava, R. Chellappa, and Abhinav Shrivastava, “Supplementary: Hierarchical Video Prediction using Relational Layouts for Human-Object Interactions.” 2021.
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@inproceedings{235691818,
title = {Supplementary: Hierarchical Video Prediction using Relational Layouts for Human-Object Interactions},
author = {{Navaneeth Bodla} and {G. Shrivastava} and {R. Chellappa} and {Abhinav Shrivastava}},
year = 2021,
booktitle = {},
url = {https://www.semanticscholar.org/paper/302e4537b277384542d7f0b5cdc4db33abbaa1db},
}

Chun Pong Lau, C. Castillo, and R. Chellappa, “ATFaceGAN: Single Face Semantic Aware Image Restoration and Recognition From Atmospheric Turbulence,” in IEEE Transactions on Biometrics Behavior and Identity Science, 2021.
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@inproceedings{232373611,
title = {ATFaceGAN: Single Face Semantic Aware Image Restoration and Recognition From Atmospheric Turbulence},
author = {{Chun Pong Lau} and {C. Castillo} and {R. Chellappa}},
year = 2021,
month = {4},
booktitle = {IEEE Transactions on Biometrics Behavior and Identity Science},
url = {https://www.semanticscholar.org/paper/d5ef84d04a6f527158d22304ff0bf73990d6563d},
}

Nanxin Chen, Shinji Watanabe, J. Villalba, Piotr Żelasko, and N. Dehak, “Non-Autoregressive Transformer for Speech Recognition,” in IEEE Signal Processing Letters, 2021.
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@inproceedings{231715684,
title = {Non-Autoregressive Transformer for Speech Recognition},
author = {{Nanxin Chen} and {Shinji Watanabe} and {J. Villalba} and {Piotr Żelasko} and {N. Dehak}},
year = 2021,
booktitle = {IEEE Signal Processing Letters},
url = {https://www.semanticscholar.org/paper/abbec7b096673b4a1f89ec20a2bf7b5bfa2c40b5},
}

Zach Wood-Doughty, I. Shpitser, and Mark Dredze, “Generating Synthetic Text Data to Evaluate Causal Inference Methods,” in arXiv.org, 2021.
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@inproceedings{231861828,
title = {Generating Synthetic Text Data to Evaluate Causal Inference Methods},
author = {{Zach Wood-Doughty} and {I. Shpitser} and {Mark Dredze}},
year = 2021,
month = {2},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/9adc1a3307c05ff3c9b0ae595cb57b1de041713f},
}

Sonal Joshi, J. Villalba, Piotr Żelasko, Laureano Moro-Vel’azquez, and N. Dehak, “Adversarial Attacks and Defenses for Speaker Identification Systems,” in arXiv.org, 2021.
[BibTeX] [Link]

@inproceedings{231693283,
title = {Adversarial Attacks and Defenses for Speaker Identification Systems},
author = {{Sonal Joshi} and {J. Villalba} and {Piotr Żelasko} and {Laureano Moro-Vel'azquez} and {N. Dehak}},
year = 2021,
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/b595a080a4376bab6edd2e8b8c4bfa3cede54f3b},
}

S. Schwarcz and R. Chellappa, “Finding Facial Forgery Artifacts with Parts-Based Detectors,” in 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2021.
[BibTeX] [Link]

@inproceedings{235703532,
title = {Finding Facial Forgery Artifacts with Parts-Based Detectors},
author = {{S. Schwarcz} and {R. Chellappa}},
year = 2021,
month = {6},
booktitle = {2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
url = {https://www.semanticscholar.org/paper/eb752fd572ca2c984b56a06c9974fdfdf951acb6},
}

Pirazh Khorramshahi, Sai Saketh Rambhatla, and R. Chellappa, “Towards Accurate Visual and Natural Language-Based Vehicle Retrieval Systems,” in 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2021.
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@inproceedings{235657291,
title = {Towards Accurate Visual and Natural Language-Based Vehicle Retrieval Systems},
author = {{Pirazh Khorramshahi} and {Sai Saketh Rambhatla} and {R. Chellappa}},
year = 2021,
month = {6},
booktitle = {2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
url = {https://www.semanticscholar.org/paper/8be99c2d0802d6222e233dd67d2927c75a0bed24},
}

Jejin Cho, J. Villalba, and N. Dehak, “The JHU submission to VoxSRC-21: Track 3,” in arXiv.org, 2021.
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@inproceedings{238198440,
title = {The JHU submission to VoxSRC-21: Track 3},
author = {{Jejin Cho} and {J. Villalba} and {N. Dehak}},
year = 2021,
month = {9},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/ed2065a9cb6f31806aba9a70a4148b99225782a3},
}

Anshul B. Shah, Shlok Kumar Mishra, Ankan Bansal, Jun-Cheng Chen, R. Chellappa, and Abhinav Shrivastava, “Pose and Joint-Aware Action Recognition – Supplementary Material.” 2021.
[BibTeX] [Link]

@inproceedings{247112044,
title = {Pose and Joint-Aware Action Recognition - Supplementary Material},
author = {{Anshul B. Shah} and {Shlok Kumar Mishra} and {Ankan Bansal} and {Jun-Cheng Chen} and {R. Chellappa} and {Abhinav Shrivastava}},
year = 2021,
booktitle = {},
url = {https://www.semanticscholar.org/paper/7400177a4165c13d22da45a242ab8180e32a3d38},
}

Piotr Żelasko, Sonal Joshi, Yiwen Shao, J. Villalba, J. Trmal, N. Dehak, and S. Khudanpur, “Adversarial Attacks and Defenses for Speech Recognition Systems,” in arXiv.org, 2021.
[BibTeX] [Link]

@inproceedings{232427815,
title = {Adversarial Attacks and Defenses for Speech Recognition Systems},
author = {{Piotr Żelasko} and {Sonal Joshi} and {Yiwen Shao} and {J. Villalba} and {J. Trmal} and {N. Dehak} and {S. Khudanpur}},
year = 2021,
month = {3},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/9d15685433a067c5beca67e5f6cc612b3dc29f66},
}

Nanxin Chen, Piotr Żelasko, L. Moro-Velázquez, J. Villalba, and N. Dehak, “Align-Denoise: Single-Pass Non-Autoregressive Speech Recognition,” in Interspeech, 2021.
[BibTeX] [Link]

@inproceedings{237634474,
title = {Align-Denoise: Single-Pass Non-Autoregressive Speech Recognition},
author = {{Nanxin Chen} and {Piotr Żelasko} and {L. Moro-Velázquez} and {J. Villalba} and {N. Dehak}},
year = 2021,
month = {8},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/2161383af6d420450f69ada26f2e310e554750f8},
}

Yunjuan Wang, Poorya Mianjy, and R. Arora, “Robust Learning for Data Poisoning Attacks,” in International Conference on Machine Learning, 2021.
[BibTeX] [Link]

@inproceedings{235826166,
title = {Robust Learning for Data Poisoning Attacks},
author = {{Yunjuan Wang} and {Poorya Mianjy} and {R. Arora}},
year = 2021,
booktitle = {International Conference on Machine Learning},
url = {https://www.semanticscholar.org/paper/c541fa104bc5297f3ebf967855d582ab9a37291d},
}

H. Inaguma, Yosuke Higuchi, Kevin Duh, Tatsuya Kawahara, and Shinji Watanabe, “Non-autoregressive End-to-end Speech Translation with Parallel Autoregressive Rescoring,” in arXiv.org, 2021.
[BibTeX] [Link]

@inproceedings{237453587,
title = {Non-autoregressive End-to-end Speech Translation with Parallel Autoregressive Rescoring},
author = {{H. Inaguma} and {Yosuke Higuchi} and {Kevin Duh} and {Tatsuya Kawahara} and {Shinji Watanabe}},
year = 2021,
month = {9},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/d79b613a67cf79740e1c08037f7d054585a12284},
}

H. Inaguma, B. Yan, S. Dalmia, P. Guo, J. Shi, K. Duh, and S. Watanabe, “ESPnet-ST IWSLT 2021 Offline Speech Translation System,” in Proceedings of the 18th International Conference on Spoken Language Translation (IWSLT 2021), Bangkok, Thailand (online), 2021, p. 100–109. doi:10.18653/v1/2021.iwslt-1.10
[BibTeX] [Abstract] [Link]

This paper describes the ESPnet-ST group{‘}s IWSLT 2021 submission in the offline speech translation track. This year we made various efforts on training data, architecture, and audio segmentation. On the data side, we investigated sequence-level knowledge distillation (SeqKD) for end-to-end (E2E) speech translation. Specifically, we used multi-referenced SeqKD from multiple teachers trained on different amounts of bitext. On the architecture side, we adopted the Conformer encoder and the Multi-Decoder architecture, which equips dedicated decoders for speech recognition and translation tasks in a unified encoder-decoder model and enables search in both source and target language spaces during inference. We also significantly improved audio segmentation by using the pyannote.audio toolkit and merging multiple short segments for long context modeling. Experimental evaluations showed that each of them contributed to large improvements in translation performance. Our best E2E system combined all the above techniques with model ensembling and achieved 31.4 BLEU on the 2-ref of tst2021 and 21.2 BLEU and 19.3 BLEU on the two single references of tst2021.

@inproceedings{inaguma-etal-2021-espnet,
title = "{ESP}net-{ST} {IWSLT} 2021 Offline Speech Translation System",
author = "Inaguma, Hirofumi and
Yan, Brian and
Dalmia, Siddharth and
Guo, Pengcheng and
Shi, Jiatong and
Duh, Kevin and
Watanabe, Shinji",
editor = "Federico, Marcello and
Waibel, Alex and
Costa-juss{\`a}, Marta R. and
Niehues, Jan and
Stuker, Sebastian and
Salesky, Elizabeth",
booktitle = "Proceedings of the 18th International Conference on Spoken Language Translation (IWSLT 2021)",
month = aug,
year = "2021",
address = "Bangkok, Thailand (online)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.iwslt-1.10",
doi = "10.18653/v1/2021.iwslt-1.10",
pages = "100--109",
abstract = "This paper describes the ESPnet-ST group{'}s IWSLT 2021 submission in the offline speech translation track. This year we made various efforts on training data, architecture, and audio segmentation. On the data side, we investigated sequence-level knowledge distillation (SeqKD) for end-to-end (E2E) speech translation. Specifically, we used multi-referenced SeqKD from multiple teachers trained on different amounts of bitext. On the architecture side, we adopted the Conformer encoder and the Multi-Decoder architecture, which equips dedicated decoders for speech recognition and translation tasks in a unified encoder-decoder model and enables search in both source and target language spaces during inference. We also significantly improved audio segmentation by using the pyannote.audio toolkit and merging multiple short segments for long context modeling. Experimental evaluations showed that each of them contributed to large improvements in translation performance. Our best E2E system combined all the above techniques with model ensembling and achieved 31.4 BLEU on the 2-ref of tst2021 and 21.2 BLEU and 19.3 BLEU on the two single references of tst2021.",
}

Alycen Wiacek, N. Dehak, and M. L. Lediju Bell, “Extending CohereNet to Retain Physical Features when Classifying Benign or Malignant Breast Masses,” in IUS, 2021.
[BibTeX] [Link]

@inproceedings{244043942,
title = {Extending CohereNet to Retain Physical Features when Classifying Benign or Malignant Breast Masses},
author = {{Alycen Wiacek} and {N. Dehak} and {M. L. Lediju Bell}},
year = 2021,
month = {9},
booktitle = {IUS},
url = {https://www.semanticscholar.org/paper/36a66d1519a846b05d014858fa611f8e9d500747},
}

Enayat Ullah, Tung Mai, Anup B. Rao, Ryan A. Rossi, and R. Arora, “Machine Unlearning via Algorithmic Stability,” in Annual Conference Computational Learning Theory, 2021.
[BibTeX] [Link]

@inproceedings{232068763,
title = {Machine Unlearning via Algorithmic Stability},
author = {{Enayat Ullah} and {Tung Mai} and {Anup B. Rao} and {Ryan A. Rossi} and {R. Arora}},
year = 2021,
month = {2},
booktitle = {Annual Conference Computational Learning Theory},
url = {https://www.semanticscholar.org/paper/0fa360d5bb8ce649155c6816fd19e5bffac4e07c},
}

R. Pappagari, Piotr Żelasko, J. Villalba, L. Moro-Velázquez, and N. Dehak, “Beyond Isolated Utterances: Conversational Emotion Recognition,” in Automatic Speech Recognition & Understanding, 2021.
[BibTeX] [Link]

@inproceedings{237492280,
title = {Beyond Isolated Utterances: Conversational Emotion Recognition},
author = {{R. Pappagari} and {Piotr Żelasko} and {J. Villalba} and {L. Moro-Velázquez} and {N. Dehak}},
year = 2021,
month = {9},
booktitle = {Automatic Speech Recognition & Understanding},
url = {https://www.semanticscholar.org/paper/6b39bd717627d97c7e69e46801fdbb38ef4eb946},
}

J. Villalba, Sonal Joshi, Piotr Żelasko, and N. Dehak, “Representation Learning to Classify and Detect Adversarial Attacks Against Speaker and Speech Recognition Systems,” in Interspeech, 2021.
[BibTeX] [Link]

@inproceedings{235790692,
title = {Representation Learning to Classify and Detect Adversarial Attacks Against Speaker and Speech Recognition Systems},
author = {{J. Villalba} and {Sonal Joshi} and {Piotr Żelasko} and {N. Dehak}},
year = 2021,
month = {7},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/8abbc820db608654c4ba10203245c191566e7286},
}

Chun Pong Lau, Amit Kumar, and R. Chellappa, “Semi-Supervised Landmark-Guided Restoration of Atmospheric Turbulent Images,” in IEEE Journal on Selected Topics in Signal Processing, 2021.
[BibTeX] [Link]

@inproceedings{232062162,
title = {Semi-Supervised Landmark-Guided Restoration of Atmospheric Turbulent Images},
author = {{Chun Pong Lau} and {Amit Kumar} and {R. Chellappa}},
year = 2021,
month = {2},
booktitle = {IEEE Journal on Selected Topics in Signal Processing},
url = {https://www.semanticscholar.org/paper/bfe23f726af27f611a81ffe2faf436ea00acb860},
}

Kevin Duh and Francisco Guzmán, “Proceedings of the 18th Biennial Machine Translation Summit (Volume 1: Research Track),” in Machine Translation Summit, 2021.
[BibTeX] [Link]

@inproceedings{237206731,
title = {Proceedings of the 18th Biennial Machine Translation Summit (Volume 1: Research Track)},
author = {{Kevin Duh} and {Francisco Guzmán}},
year = 2021,
booktitle = {Machine Translation Summit},
url = {https://www.semanticscholar.org/paper/a693afc22d8cf7cbdf824a774c1c17195ae4c371},
}

Sonal Joshi, J. Villalba, Piotr Żelasko, L. Moro-Velázquez, and N. Dehak, “Study of Pre-Processing Defenses Against Adversarial Attacks on State-of-the-Art Speaker Recognition Systems,” in IEEE Transactions on Information Forensics and Security, 2021.
[BibTeX] [Link]

@inproceedings{235652468,
title = {Study of Pre-Processing Defenses Against Adversarial Attacks on State-of-the-Art Speaker Recognition Systems},
author = {{Sonal Joshi} and {J. Villalba} and {Piotr Żelasko} and {L. Moro-Velázquez} and {N. Dehak}},
year = 2021,
month = {1},
booktitle = {IEEE Transactions on Information Forensics and Security},
url = {https://www.semanticscholar.org/paper/46a3c701f9e013b9aba1e6f6d5dc3ff0998573a2},
}

Jaejin Cho, Piotr Żelasko, J. Villalba, and N. Dehak, “Improving Reconstruction Loss Based Speaker Embedding in Unsupervised and Semi-Supervised Scenarios,” in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2021.
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@inproceedings{235780607,
title = {Improving Reconstruction Loss Based Speaker Embedding in Unsupervised and Semi-Supervised Scenarios},
author = {{Jaejin Cho} and {Piotr Żelasko} and {J. Villalba} and {N. Dehak}},
year = 2021,
month = {6},
booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
url = {https://www.semanticscholar.org/paper/2695593c166924372283e2a5802f7bca4c17a356},
}

Liming Wang, Xinsheng Wang, M. Hasegawa-Johnson, O. Scharenborg, and N. Dehak, “Align or attend? Toward More Efficient and Accurate Spoken Word Discovery Using Speech-to-Image Retrieval,” in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2021.
[BibTeX] [Link]

@inproceedings{235223299,
title = {Align or attend? Toward More Efficient and Accurate Spoken Word Discovery Using Speech-to-Image Retrieval},
author = {{Liming Wang} and {Xinsheng Wang} and {M. Hasegawa-Johnson} and {O. Scharenborg} and {N. Dehak}},
year = 2021,
month = {6},
booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
url = {https://www.semanticscholar.org/paper/70c65b5b0b2debec53c631ab99f0f6a01a86602c},
}

R. Pappagari, Jaejin Cho, Sonal Joshi, L. Moro-Velázquez, Piotr Żelasko, J. Villalba, and N. Dehak, “Automatic Detection and Assessment of Alzheimer Disease Using Speech and Language Technologies in Low-Resource Scenarios,” in Interspeech, 2021.
[BibTeX] [Link]

@inproceedings{239653935,
title = {Automatic Detection and Assessment of Alzheimer Disease Using Speech and Language Technologies in Low-Resource Scenarios},
author = {{R. Pappagari} and {Jaejin Cho} and {Sonal Joshi} and {L. Moro-Velázquez} and {Piotr Żelasko} and {J. Villalba} and {N. Dehak}},
year = 2021,
month = {8},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/7e3deabd44eccb0fe2823d8cecf1e182efeeb0f6},
}

Prithviraj Dhar, Joshua Gleason, A. Roy, C. Castillo, and R. Chellappa, “Supplementary Material – PASS.” 2021.
[BibTeX] [Link]

@inproceedings{244312236,
title = {Supplementary Material - PASS},
author = {{Prithviraj Dhar} and {Joshua Gleason} and {A. Roy} and {C. Castillo} and {R. Chellappa}},
year = 2021,
booktitle = {},
url = {https://www.semanticscholar.org/paper/ee50fa46cd195e4b59330297d4285877906583b5},
}

Yuval Pinter, A. Stent, Mark Dredze, and Jacob Eisenstein, “Learning to Look Inside: Augmenting Token-Based Encoders with Character-Level Information,” in arXiv.org, 2021.
[BibTeX] [Link]

@inproceedings{236771967,
title = {Learning to Look Inside: Augmenting Token-Based Encoders with Character-Level Information},
author = {{Yuval Pinter} and {A. Stent} and {Mark Dredze} and {Jacob Eisenstein}},
year = 2021,
month = {8},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/9c2e4e5ee224c20a45c37244924138b50f3fe603},
}

Jonah P. Sengupta, M. Villemur, and A. Andreou, “A Spike-based Cellular-Neural Network Architecture for Spatiotemporal filtering,” in Annual Conference on Information Sciences and Systems, 2021.
[BibTeX] [Link]

@inproceedings{233333189,
title = {A Spike-based Cellular-Neural Network Architecture for Spatiotemporal filtering},
author = {{Jonah P. Sengupta} and {M. Villemur} and {A. Andreou}},
year = 2021,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/76791fe786d8fd412ee15ca19b65c8e5b3103bc1},
}

N. Balachandran, Jun-Cheng Chen, and R. Chellappa, “LR-to-HR Face Hallucination with an Adversarial Progressive Attribute-Induced Network,” in arXiv.org, 2021.
[BibTeX] [Link]

@inproceedings{238226971,
title = {LR-to-HR Face Hallucination with an Adversarial Progressive Attribute-Induced Network},
author = {{N. Balachandran} and {Jun-Cheng Chen} and {R. Chellappa}},
year = 2021,
month = {9},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/c741349663272c0d4a61e52d5650ba123bbbc81e},
}

Sai Saketh Rambhatla, Michael Jones, and R. Chellappa, “To Boost or not to Boost: On the Limits of Boosted Neural Networks,” in arXiv.org, 2021.
[BibTeX] [Link]

@inproceedings{236493542,
title = {To Boost or not to Boost: On the Limits of Boosted Neural Networks},
author = {{Sai Saketh Rambhatla} and {Michael Jones} and {R. Chellappa}},
year = 2021,
month = {7},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/cf94610981c556cc8e8930c6f71f88f2186d446f},
}

Jalaj Upadhyay, Sarvagya Upadhyay, and R. Arora, “Di ↵ erentially Private Analysis on Graph Streams.” 2021.
[BibTeX] [Link]

@inproceedings{233236129,
title = {Di ↵ erentially Private Analysis on Graph Streams},
author = {{Jalaj Upadhyay} and {Sarvagya Upadhyay} and {R. Arora}},
year = 2021,
booktitle = {},
url = {https://www.semanticscholar.org/paper/b68d4f1c7010b52a3468168ab332abe548f0e14f},
}

Nanxin Chen, Yu Zhang, H. Zen, Ron J. Weiss, Mohammad Norouzi, N. Dehak, and William Chan, “WaveGrad 2: Iterative Refinement for Text-to-Speech Synthesis,” in Interspeech, 2021.
[BibTeX] [Link]

@inproceedings{235458124,
title = {WaveGrad 2: Iterative Refinement for Text-to-Speech Synthesis},
author = {{Nanxin Chen} and {Yu Zhang} and {H. Zen} and {Ron J. Weiss} and {Mohammad Norouzi} and {N. Dehak} and {William Chan}},
year = 2021,
month = {6},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/10ae9a3d1e0874a50820766bd414f98e095cdd8a},
}

Piotr Żelasko, R. Pappagari, and N. Dehak, “What Helps Transformers Recognize Conversational Structure? Importance of Context, Punctuation, and Labels in Dialog Act Recognition,” in Transactions of the Association for Computational Linguistics, 2021.
[BibTeX] [Link]

@inproceedings{235742745,
title = {What Helps Transformers Recognize Conversational Structure? Importance of Context, Punctuation, and Labels in Dialog Act Recognition},
author = {{Piotr Żelasko} and {R. Pappagari} and {N. Dehak}},
year = 2021,
month = {7},
booktitle = {Transactions of the Association for Computational Linguistics},
url = {https://www.semanticscholar.org/paper/f3173cd86ae95a53f44f0d1093e85df4988a459a},
}

L. Moro-Velázquez, Jorge Andrés Gómez García, J. D. Arias-Londoño, N. Dehak, and Juan Ignacio Godino-Llorente, “Advances in Parkinson’s Disease detection and assessment using voice and speech: A review of the articulatory and phonatory aspects,” in Biomedical Signal Processing and Control, 2021.
[BibTeX] [Link]

@inproceedings{233261144,
title = {Advances in Parkinson's Disease detection and assessment using voice and speech: A review of the articulatory and phonatory aspects},
author = {{L. Moro-Velázquez} and {Jorge Andrés Gómez García} and {J. D. Arias-Londoño} and {N. Dehak} and {Juan Ignacio Godino-Llorente}},
year = 2021,
booktitle = {Biomedical Signal Processing and Control},
url = {https://www.semanticscholar.org/paper/e05b3799939621e0dd12cfe2a10f21788c6f4293},
}

Ankan Bansal, Jingxiao Zheng, and R. Chellappa, “Face Recognition from Still Images and Video,” in Encyclopedia of Cryptography, Security and Privacy, 2021.
[BibTeX] [Link]

@inproceedings{243104926,
title = {Face Recognition from Still Images and Video},
author = {{Ankan Bansal} and {Jingxiao Zheng} and {R. Chellappa}},
year = 2021,
booktitle = {Encyclopedia of Cryptography, Security and Privacy},
url = {https://www.semanticscholar.org/paper/eddee7bdc03d5973cd98303c0d5850bc433069c1},
}

Daniel R. Mendat, Jonah P. Sengupta, Drake K. Foreman, and A. Andreou, “Parallel Computation of Event-Based Visual Features Using Relational Graphs,” in Annual Conference on Information Sciences and Systems, 2021.
[BibTeX] [Link]

@inproceedings{233332283,
title = {Parallel Computation of Event-Based Visual Features Using Relational Graphs},
author = {{Daniel R. Mendat} and {Jonah P. Sengupta} and {Drake K. Foreman} and {A. Andreou}},
year = 2021,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/e00046bd84c1efded8589ee44d907f385d4b7e99},
}

Cheng Peng, Haofu Liao, G. Wong, Jiebo Luo, S. Zhou, and R. Chellappa, “XraySyn: Realistic View Synthesis From a Single Radiograph Through CT Priors,” in AAAI Conference on Artificial Intelligence, 2020.
[BibTeX] [Link]

@inproceedings{227305790,
title = {XraySyn: Realistic View Synthesis From a Single Radiograph Through CT Priors},
author = {{Cheng Peng} and {Haofu Liao} and {G. Wong} and {Jiebo Luo} and {S. Zhou} and {R. Chellappa}},
year = 2020,
month = {12},
booktitle = {AAAI Conference on Artificial Intelligence},
url = {https://www.semanticscholar.org/paper/dbe6bff16563ba3b821f8fd5a93d298d0fd9517a},
}

Ilya Kavalerov, Weilin Li, W. Czaja, and R. Chellappa, “3-D Fourier Scattering Transform and Classification of Hyperspectral Images,” in IEEE Transactions on Geoscience and Remote Sensing, 2020.
[BibTeX] [Link]

@inproceedings{234523589,
title = {3-D Fourier Scattering Transform and Classification of Hyperspectral Images},
author = {{Ilya Kavalerov} and {Weilin Li} and {W. Czaja} and {R. Chellappa}},
year = 2020,
month = {12},
booktitle = {IEEE Transactions on Geoscience and Remote Sensing},
url = {https://www.semanticscholar.org/paper/74b6910c70e9990b06b6ec9a55b976765b238a16},
}

H. Mei, T. Wan, and J. Eisner, “Noise-Contrastive Estimation for Multivariate Point Processes,” in Advances in Neural Information Processing Systems (NeurIPS), 2020, p. 5204–5214.
[BibTeX] [Link]

@InProceedings{mei-wan-eisner-2020,
author = "Hongyuan Mei and Tom Wan and Jason Eisner",
title = "Noise-Contrastive Estimation for Multivariate Point
Processes",
booktitle = "Advances in Neural Information Processing Systems
(NeurIPS)",
pages = "5204--5214",
year = "2020",
month = dec,
URL = "http://cs.jhu.edu/~jason/papers/#mei-wan-eisner-2020",
}

K. Marchisio, K. Duh, and P. Koehn, “When Does Unsupervised Machine Translation Work?,” in Proceedings of the Fifth Conference on Machine Translation, Online, 2020, p. 571–583.
[BibTeX] [Abstract] [Link]

Despite the reported success of unsupervised machine translation (MT), the field has yet to examine the conditions under which the methods succeed and fail. We conduct an extensive empirical evaluation using dissimilar language pairs, dissimilar domains, and diverse datasets. We find that performance rapidly deteriorates when source and target corpora are from different domains, and that stochasticity during embedding training can dramatically affect downstream results. We additionally find that unsupervised MT performance declines when source and target languages use different scripts, and observe very poor performance on authentic low-resource language pairs. We advocate for extensive empirical evaluation of unsupervised MT systems to highlight failure points and encourage continued research on the most promising paradigms. We release our preprocessed dataset to encourage evaluations that stress-test systems under multiple data conditions.

@inproceedings{marchisio-etal-2020-unsupervised,
title = "When Does Unsupervised Machine Translation Work?",
author = "Marchisio, Kelly and
Duh, Kevin and
Koehn, Philipp",
editor = {Barrault, Lo{\"\i}c and
Bojar, Ond{\v{r}}ej and
Bougares, Fethi and
Chatterjee, Rajen and
Costa-juss{\`a}, Marta R. and
Federmann, Christian and
Fishel, Mark and
Fraser, Alexander and
Graham, Yvette and
Guzman, Paco and
Haddow, Barry and
Huck, Matthias and
Yepes, Antonio Jimeno and
Koehn, Philipp and
Martins, Andr{\'e} and
Morishita, Makoto and
Monz, Christof and
Nagata, Masaaki and
Nakazawa, Toshiaki and
Negri, Matteo},
booktitle = "Proceedings of the Fifth Conference on Machine Translation",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.wmt-1.68",
pages = "571--583",
abstract = "Despite the reported success of unsupervised machine translation (MT), the field has yet to examine the conditions under which the methods succeed and fail. We conduct an extensive empirical evaluation using dissimilar language pairs, dissimilar domains, and diverse datasets. We find that performance rapidly deteriorates when source and target corpora are from different domains, and that stochasticity during embedding training can dramatically affect downstream results. We additionally find that unsupervised MT performance declines when source and target languages use different scripts, and observe very poor performance on authentic low-resource language pairs. We advocate for extensive empirical evaluation of unsupervised MT systems to highlight failure points and encourage continued research on the most promising paradigms. We release our preprocessed dataset to encourage evaluations that stress-test systems under multiple data conditions.",
}

S. Sun and K. Duh, “CLIRMatrix: A massively large collection of bilingual and multilingual datasets for Cross-Lingual Information Retrieval,” in Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), Online, 2020, p. 4160–4170. doi:10.18653/v1/2020.emnlp-main.340
[BibTeX] [Abstract] [Link]

We present CLIRMatrix, a massively large collection of bilingual and multilingual datasets for Cross-Lingual Information Retrieval extracted automatically from Wikipedia. CLIRMatrix comprises (1) BI-139, a bilingual dataset of queries in one language matched with relevant documents in another language for 139×138=19,182 language pairs, and (2) MULTI-8, a multilingual dataset of queries and documents jointly aligned in 8 different languages. In total, we mined 49 million unique queries and 34 billion (query, document, label) triplets, making it the largest and most comprehensive CLIR dataset to date. This collection is intended to support research in end-to-end neural information retrieval and is publicly available at [url]. We provide baseline neural model results on BI-139, and evaluate MULTI-8 in both single-language retrieval and mix-language retrieval settings.

@inproceedings{sun-duh-2020-clirmatrix,
title = "{CLIRM}atrix: A massively large collection of bilingual and multilingual datasets for Cross-Lingual Information Retrieval",
author = "Sun, Shuo and
Duh, Kevin",
editor = "Webber, Bonnie and
Cohn, Trevor and
He, Yulan and
Liu, Yang",
booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.emnlp-main.340",
doi = "10.18653/v1/2020.emnlp-main.340",
pages = "4160--4170",
abstract = "We present CLIRMatrix, a massively large collection of bilingual and multilingual datasets for Cross-Lingual Information Retrieval extracted automatically from Wikipedia. CLIRMatrix comprises (1) BI-139, a bilingual dataset of queries in one language matched with relevant documents in another language for 139x138=19,182 language pairs, and (2) MULTI-8, a multilingual dataset of queries and documents jointly aligned in 8 different languages. In total, we mined 49 million unique queries and 34 billion (query, document, label) triplets, making it the largest and most comprehensive CLIR dataset to date. This collection is intended to support research in end-to-end neural information retrieval and is publicly available at [url]. We provide baseline neural model results on BI-139, and evaluate MULTI-8 in both single-language retrieval and mix-language retrieval settings.",
}

S. Wu and M. Dredze, “Do Explicit Alignments Robustly Improve Multilingual Encoders?,” in Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), Online, 2020, p. 4471–4482. doi:10.18653/v1/2020.emnlp-main.362
[BibTeX] [Abstract] [Link]

Multilingual BERT (mBERT), XLM-RoBERTa (XLMR) and other unsupervised multilingual encoders can effectively learn cross-lingual representation. Explicit alignment objectives based on bitexts like Europarl or MultiUN have been shown to further improve these representations. However, word-level alignments are often suboptimal and such bitexts are unavailable for many languages. In this paper, we propose a new contrastive alignment objective that can better utilize such signal, and examine whether these previous alignment methods can be adapted to noisier sources of aligned data: a randomly sampled 1 million pair subset of the OPUS collection. Additionally, rather than report results on a single dataset with a single model run, we report the mean and standard derivation of multiple runs with different seeds, on four datasets and tasks. Our more extensive analysis finds that, while our new objective outperforms previous work, overall these methods do not improve performance with a more robust evaluation framework. Furthermore, the gains from using a better underlying model eclipse any benefits from alignment training. These negative results dictate more care in evaluating these methods and suggest limitations in applying explicit alignment objectives.

@inproceedings{wu-dredze-2020-explicit,
title = "Do Explicit Alignments Robustly Improve Multilingual Encoders?",
author = "Wu, Shijie and
Dredze, Mark",
editor = "Webber, Bonnie and
Cohn, Trevor and
He, Yulan and
Liu, Yang",
booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.emnlp-main.362",
doi = "10.18653/v1/2020.emnlp-main.362",
pages = "4471--4482",
abstract = "Multilingual BERT (mBERT), XLM-RoBERTa (XLMR) and other unsupervised multilingual encoders can effectively learn cross-lingual representation. Explicit alignment objectives based on bitexts like Europarl or MultiUN have been shown to further improve these representations. However, word-level alignments are often suboptimal and such bitexts are unavailable for many languages. In this paper, we propose a new contrastive alignment objective that can better utilize such signal, and examine whether these previous alignment methods can be adapted to noisier sources of aligned data: a randomly sampled 1 million pair subset of the OPUS collection. Additionally, rather than report results on a single dataset with a single model run, we report the mean and standard derivation of multiple runs with different seeds, on four datasets and tasks. Our more extensive analysis finds that, while our new objective outperforms previous work, overall these methods do not improve performance with a more robust evaluation framework. Furthermore, the gains from using a better underlying model eclipse any benefits from alignment training. These negative results dictate more care in evaluating these methods and suggest limitations in applying explicit alignment objectives.",
}

Rachel Dorn, A. Nobles, Masoud Rouhizadeh, and Mark Dredze, “Examining the Feasibility of Off-the-Shelf Algorithms for Masking Directly Identifiable Information in Social Media Data,” in arXiv.org, 2020.
[BibTeX] [Link]

@inproceedings{226975724,
title = {Examining the Feasibility of Off-the-Shelf Algorithms for Masking Directly Identifiable Information in Social Media Data},
author = {{Rachel Dorn} and {A. Nobles} and {Masoud Rouhizadeh} and {Mark Dredze}},
year = 2020,
month = {11},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/3d35c0aec777f6c180d4bf61a2443ec35230bfd2},
}

K. Harrigian, C. Aguirre, and M. Dredze, “Do Models of Mental Health Based on Social Media Data Generalize?,” in Findings of the Association for Computational Linguistics: EMNLP 2020, Online, 2020, p. 3774–3788. doi:10.18653/v1/2020.findings-emnlp.337
[BibTeX] [Abstract] [Link]

Proxy-based methods for annotating mental health status in social media have grown popular in computational research due to their ability to gather large training samples. However, an emerging body of literature has raised new concerns regarding the validity of these types of methods for use in clinical applications. To further understand the robustness of distantly supervised mental health models, we explore the generalization ability of machine learning classifiers trained to detect depression in individuals across multiple social media platforms. Our experiments not only reveal that substantial loss occurs when transferring between platforms, but also that there exist several unreliable confounding factors that may enable researchers to overestimate classification performance. Based on these results, we enumerate recommendations for future mental health dataset construction.

@inproceedings{harrigian-etal-2020-models,
title = "Do Models of Mental Health Based on Social Media Data Generalize?",
author = "Harrigian, Keith and
Aguirre, Carlos and
Dredze, Mark",
editor = "Cohn, Trevor and
He, Yulan and
Liu, Yang",
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2020",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.findings-emnlp.337",
doi = "10.18653/v1/2020.findings-emnlp.337",
pages = "3774--3788",
abstract = "Proxy-based methods for annotating mental health status in social media have grown popular in computational research due to their ability to gather large training samples. However, an emerging body of literature has raised new concerns regarding the validity of these types of methods for use in clinical applications. To further understand the robustness of distantly supervised mental health models, we explore the generalization ability of machine learning classifiers trained to detect depression in individuals across multiple social media platforms. Our experiments not only reveal that substantial loss occurs when transferring between platforms, but also that there exist several unreliable confounding factors that may enable researchers to overestimate classification performance. Based on these results, we enumerate recommendations for future mental health dataset construction.",
}

Nanxin Chen, Piotr Żelasko, J. Villalba, and N. Dehak, “Focus on the Present: A Regularization Method for the ASR Source-Target Attention Layer,” in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2020.
[BibTeX] [Link]

@inproceedings{226236802,
title = {Focus on the Present: A Regularization Method for the ASR Source-Target Attention Layer},
author = {{Nanxin Chen} and {Piotr Żelasko} and {J. Villalba} and {N. Dehak}},
year = 2020,
month = {11},
booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
url = {https://www.semanticscholar.org/paper/f90f383a3f027bfa48fea68790d3cb77f7634b92},
}

Jesús Antonio Villalba López, D. Garcia-Romero, Nanxin Chen, Gregory Sell, Jonas Borgstrom, A. McCree, Leibny Paola García-Perera, Saurabh Kataria, P. S. Nidadavolu, Pedro Torres-Carrasquiilo, and N. Dehak, “Advances in Speaker Recognition for Telephone and Audio-Visual Data: the JHU-MIT Submission for NIST SRE19,” in The Speaker and Language Recognition Workshop, 2020.
[BibTeX] [Link]

@inproceedings{219505334,
title = {Advances in Speaker Recognition for Telephone and Audio-Visual Data: the JHU-MIT Submission for NIST SRE19},
author = {{Jesús Antonio Villalba López} and {D. Garcia-Romero} and {Nanxin Chen} and {Gregory Sell} and {Jonas Borgstrom} and {A. McCree} and {Leibny Paola García-Perera} and {Saurabh Kataria} and {P. S. Nidadavolu} and {Pedro Torres-Carrasquiilo} and {N. Dehak}},
year = 2020,
month = {11},
booktitle = {The Speaker and Language Recognition Workshop},
url = {https://www.semanticscholar.org/paper/de00fffe4b64aef3797e05e74b5d3d07065b20ee},
}

R. Pappagari, J. Villalba, Piotr Żelasko, L. Moro-Velázquez, and N. Dehak, “CopyPaste: An Augmentation Method for Speech Emotion Recognition,” in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2020.
[BibTeX] [Link]

@inproceedings{225094487,
title = {CopyPaste: An Augmentation Method for Speech Emotion Recognition},
author = {{R. Pappagari} and {J. Villalba} and {Piotr Żelasko} and {L. Moro-Velázquez} and {N. Dehak}},
year = 2020,
month = {10},
booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
url = {https://www.semanticscholar.org/paper/f620d71fccdf3efad7be1748d40eaadea5c9d6dd},
}

R. Pappagari, Jaejin Cho, L. Moro-Velázquez, and N. Dehak, “Using State of the Art Speaker Recognition and Natural Language Processing Technologies to Detect Alzheimer’s Disease and Assess its Severity,” in Interspeech, 2020.
[BibTeX] [Link]

@inproceedings{226203271,
title = {Using State of the Art Speaker Recognition and Natural Language Processing Technologies to Detect Alzheimer's Disease and Assess its Severity},
author = {{R. Pappagari} and {Jaejin Cho} and {L. Moro-Velázquez} and {N. Dehak}},
year = 2020,
month = {10},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/4c25acf91e0b0b475e69cb9ab9f0041d16bc7c7d},
}

Jaejin Cho, Piotr Żelasko, J. Villalba, Shinji Watanabe, and N. Dehak, “Learning Speaker Embedding from Text-to-Speech,” in Interspeech, 2020.
[BibTeX] [Link]

@inproceedings{225039997,
title = {Learning Speaker Embedding from Text-to-Speech},
author = {{Jaejin Cho} and {Piotr Żelasko} and {J. Villalba} and {Shinji Watanabe} and {N. Dehak}},
year = 2020,
month = {10},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/faf494d0aa25a17aa25930ffb4c750fa59c44849},
}

J. Villalba, Yuekai Zhang, and N. Dehak, “x-Vectors Meet Adversarial Attacks: Benchmarking Adversarial Robustness in Speaker Verification,” in Interspeech, 2020.
[BibTeX] [Link]

@inproceedings{226200412,
title = {x-Vectors Meet Adversarial Attacks: Benchmarking Adversarial Robustness in Speaker Verification},
author = {{J. Villalba} and {Yuekai Zhang} and {N. Dehak}},
year = 2020,
month = {10},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/1b305dbfb789a19013d7ab8fa4f26ab33d99f6ed},
}

Siyuan Feng, Piotr Żelasko, Laureano Moro-Vel’azquez, A. Abavisani, M. Hasegawa-Johnson, O. Scharenborg, and N. Dehak, “How Phonotactics Affect Multilingual and Zero-Shot ASR Performance,” in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2020.
[BibTeX] [Link]

@inproceedings{225062469,
title = {How Phonotactics Affect Multilingual and Zero-Shot ASR Performance},
author = {{Siyuan Feng} and {Piotr Żelasko} and {Laureano Moro-Vel'azquez} and {A. Abavisani} and {M. Hasegawa-Johnson} and {O. Scharenborg} and {N. Dehak}},
year = 2020,
month = {10},
booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
url = {https://www.semanticscholar.org/paper/2fb642dc5d724c32d3b4cfa2359432968d591287},
}

Poorya Mianjy and R. Arora, “On Convergence and Generalization of Dropout Training,” in Neural Information Processing Systems, 2020.
[BibTeX] [Link]

@inproceedings{225068823,
title = {On Convergence and Generalization of Dropout Training},
author = {{Poorya Mianjy} and {R. Arora}},
year = 2020,
month = {10},
booktitle = {Neural Information Processing Systems},
url = {https://www.semanticscholar.org/paper/2d9dc4b6228ca78f395bd55be79b26e02fcb608b},
}

Yuekai Zhang, Ziyan Jiang, J. Villalba, and N. Dehak, “Black-Box Attacks on Spoofing Countermeasures Using Transferability of Adversarial Examples,” in Interspeech, 2020.
[BibTeX] [Link]

@inproceedings{226202223,
title = {Black-Box Attacks on Spoofing Countermeasures Using Transferability of Adversarial Examples},
author = {{Yuekai Zhang} and {Ziyan Jiang} and {J. Villalba} and {N. Dehak}},
year = 2020,
month = {10},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/cf1e3bf91fa9989981e5ed3e00331ff0dbe3d56f},
}

E. Leas, E. M. Hendrickson, A. Nobles, R. Todd, Davey M. Smith, Mark Dredze, and J. Ayers, “Self-reported Cannabidiol (CBD) Use for Conditions With Proven Therapies,” in JAMA Network Open, 2020.
[BibTeX] [Link]

@inproceedings{222834475,
title = {Self-reported Cannabidiol (CBD) Use for Conditions With Proven Therapies},
author = {{E. Leas} and {E. M. Hendrickson} and {A. Nobles} and {R. Todd} and {Davey M. Smith} and {Mark Dredze} and {J. Ayers}},
year = 2020,
month = {10},
booktitle = {JAMA Network Open},
url = {https://www.semanticscholar.org/paper/43da600949c62a5cb2a54f427ddfa468167a3243},
}

E. Leas, A. Nobles, Theodore L. Caputi, Mark Dredze, Shu-Hong Zhu, Joanna E. Cohen, and J. Ayers, “News coverage of the E-cigarette, or Vaping, product use Associated Lung Injury (EVALI) outbreak and internet searches for vaping cessation,” in Tobacco Control, 2020.
[BibTeX] [Link]

@inproceedings{222354379,
title = {News coverage of the E-cigarette, or Vaping, product use Associated Lung Injury (EVALI) outbreak and internet searches for vaping cessation},
author = {{E. Leas} and {A. Nobles} and {Theodore L. Caputi} and {Mark Dredze} and {Shu-Hong Zhu} and {Joanna E. Cohen} and {J. Ayers}},
year = 2020,
month = {10},
booktitle = {Tobacco Control},
url = {https://www.semanticscholar.org/paper/22c3117fc4fa28bef30d00843035d604ee1dc0c4},
}

J. Naradowsky, X. Zhang, and K. Duh, “Machine Translation System Selection from Bandit Feedback,” in Proceedings of the 14th Conference of the Association for Machine Translation in the Americas (Volume 1: Research Track), Virtual, 2020, p. 50–63.
[BibTeX] [Link]

@inproceedings{naradowsky-etal-2020-machine,
title = "Machine Translation System Selection from Bandit Feedback",
author = "Naradowsky, Jason and
Zhang, Xuan and
Duh, Kevin",
editor = "Denkowski, Michael and
Federmann, Christian",
booktitle = "Proceedings of the 14th Conference of the Association for Machine Translation in the Americas (Volume 1: Research Track)",
month = oct,
year = "2020",
address = "Virtual",
publisher = "Association for Machine Translation in the Americas",
url = "https://aclanthology.org/2020.amta-research.5",
pages = "50--63",
}

H. Inaguma, Yosuke Higuchi, Kevin Duh, Tatsuya Kawahara, and Shinji Watanabe, “ORTHROS: non-autoregressive end-to-end speech translation With dual-decoder,” in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2020.
[BibTeX] [Link]

@inproceedings{225069289,
title = {ORTHROS: non-autoregressive end-to-end speech translation With dual-decoder},
author = {{H. Inaguma} and {Yosuke Higuchi} and {Kevin Duh} and {Tatsuya Kawahara} and {Shinji Watanabe}},
year = 2020,
month = {10},
booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
url = {https://www.semanticscholar.org/paper/589e651c69251ee20a89e075d015eb03b35cf17d},
}

Saurabh Kataria, J. Villalba, and N. Dehak, “Perceptual Loss Based Speech Denoising with an Ensemble of Audio Pattern Recognition and Self-Supervised Models,” in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2020.
[BibTeX] [Link]

@inproceedings{225039829,
title = {Perceptual Loss Based Speech Denoising with an Ensemble of Audio Pattern Recognition and Self-Supervised Models},
author = {{Saurabh Kataria} and {J. Villalba} and {N. Dehak}},
year = 2020,
month = {10},
booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
url = {https://www.semanticscholar.org/paper/af803a305d5f1b079bb55a9f0ceeb5acf3726a1a},
}

Amelia M. Jamison, David A. Broniatowski, Michael C. Smith, Kajal Parikh, Adeena Malik, Mark Dredze, and S. Quinn, “Adapting and Extending a Typology to Identify Vaccine Misinformation on Twitter.,” in American Journal of Public Health, 2020.
[BibTeX] [Link]

@inproceedings{222152020,
title = {Adapting and Extending a Typology to Identify Vaccine Misinformation on Twitter.},
author = {{Amelia M. Jamison} and {David A. Broniatowski} and {Michael C. Smith} and {Kajal Parikh} and {Adeena Malik} and {Mark Dredze} and {S. Quinn}},
year = 2020,
month = {10},
booktitle = {American Journal of Public Health},
url = {https://www.semanticscholar.org/paper/8aceab6f7c62f65667094060b79b7ac735ae7f3a},
}

David A. Broniatowski, Amelia M. Jamison, N. Johnson, N. Velásquez, R. Leahy, N. J. Restrepo, Mark Dredze, and S. Quinn, “Facebook Pages, the “Disneyland” Measles Outbreak, and Promotion of Vaccine Refusal as a Civil Right, 2009-2019.,” in American Journal of Public Health, 2020.
[BibTeX] [Link]

@inproceedings{222154979,
title = {Facebook Pages, the "Disneyland" Measles Outbreak, and Promotion of Vaccine Refusal as a Civil Right, 2009-2019.},
author = {{David A. Broniatowski} and {Amelia M. Jamison} and {N. Johnson} and {N. Velásquez} and {R. Leahy} and {N. J. Restrepo} and {Mark Dredze} and {S. Quinn}},
year = 2020,
month = {10},
booktitle = {American Journal of Public Health},
url = {https://www.semanticscholar.org/paper/77f452950894994f55dae8a4cfbdf4cd1980fc59},
}

J. Ayers, B. Althouse, Adam Poliak, E. Leas, A. Nobles, Mark Dredze, and Davey M. Smith, “Quantifying Public Interest in Police Reforms by Mining Internet Search Data Following George Floyd’s Death,” in Journal of Medical Internet Research, 2020.
[BibTeX] [Link]

@inproceedings{224829138,
title = {Quantifying Public Interest in Police Reforms by Mining Internet Search Data Following George Floyd’s Death},
author = {{J. Ayers} and {B. Althouse} and {Adam Poliak} and {E. Leas} and {A. Nobles} and {Mark Dredze} and {Davey M. Smith}},
year = 2020,
month = {10},
booktitle = {Journal of Medical Internet Research},
url = {https://www.semanticscholar.org/paper/53dfb4e46c47b98a11ca5fc94db5dc55c42243ee},
}

Jeremias Sulam, Ramchandran Muthumukar, and R. Arora, “Adversarial Robustness of Supervised Sparse Coding,” in Neural Information Processing Systems, 2020.
[BibTeX] [Link]

@inproceedings{225062156,
title = {Adversarial Robustness of Supervised Sparse Coding},
author = {{Jeremias Sulam} and {Ramchandran Muthumukar} and {R. Arora}},
year = 2020,
month = {10},
booktitle = {Neural Information Processing Systems},
url = {https://www.semanticscholar.org/paper/07cc4408d5fa28007db9135fceb73943a713a962},
}

H. Inaguma, S. Kiyono, K. Duh, S. Karita, N. Yalta, T. Hayashi, and S. Watanabe, “ESPnet-ST: All-in-One Speech Translation Toolkit,” in Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations, Online, 2020, p. 302–311. doi:10.18653/v1/2020.acl-demos.34
[BibTeX] [Abstract] [Link]

We present ESPnet-ST, which is designed for the quick development of speech-to-speech translation systems in a single framework. ESPnet-ST is a new project inside end-to-end speech processing toolkit, ESPnet, which integrates or newly implements automatic speech recognition, machine translation, and text-to-speech functions for speech translation. We provide all-in-one recipes including data pre-processing, feature extraction, training, and decoding pipelines for a wide range of benchmark datasets. Our reproducible results can match or even outperform the current state-of-the-art performances; these pre-trained models are downloadable. The toolkit is publicly available at \url{https://github.com/espnet/espnet}.

@inproceedings{inaguma-etal-2020-espnet,
title = "{ESP}net-{ST}: All-in-One Speech Translation Toolkit",
author = "Inaguma, Hirofumi and
Kiyono, Shun and
Duh, Kevin and
Karita, Shigeki and
Yalta, Nelson and
Hayashi, Tomoki and
Watanabe, Shinji",
editor = "Celikyilmaz, Asli and
Wen, Tsung-Hsien",
booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations",
month = jul,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.acl-demos.34",
doi = "10.18653/v1/2020.acl-demos.34",
pages = "302--311",
abstract = "We present ESPnet-ST, which is designed for the quick development of speech-to-speech translation systems in a single framework. ESPnet-ST is a new project inside end-to-end speech processing toolkit, ESPnet, which integrates or newly implements automatic speech recognition, machine translation, and text-to-speech functions for speech translation. We provide all-in-one recipes including data pre-processing, feature extraction, training, and decoding pipelines for a wide range of benchmark datasets. Our reproducible results can match or even outperform the current state-of-the-art performances; these pre-trained models are downloadable. The toolkit is publicly available at \url{https://github.com/espnet/espnet}.",
}

E. Schumacher, A. Mulyar, and M. Dredze, “Clinical Concept Linking with Contextualized Neural Representations,” in Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, Online, 2020, p. 8585–8592. doi:10.18653/v1/2020.acl-main.760
[BibTeX] [Abstract] [Link]

In traditional approaches to entity linking, linking decisions are based on three sources of information {–} the similarity of the mention string to an entity{‘}s name, the similarity of the context of the document to the entity, and broader information about the knowledge base (KB). In some domains, there is little contextual information present in the KB and thus we rely more heavily on mention string similarity. We consider one example of this, concept linking, which seeks to link mentions of medical concepts to a medical concept ontology. We propose an approach to concept linking that leverages recent work in contextualized neural models, such as ELMo (Peters et al. 2018), which create a token representation that integrates the surrounding context of the mention and concept name. We find a neural ranking approach paired with contextualized embeddings provides gains over a competitive baseline (Leaman et al. 2013). Additionally, we find that a pre-training step using synonyms from the ontology offers a useful initialization for the ranker.

@inproceedings{schumacher-etal-2020-clinical,
title = "Clinical Concept Linking with Contextualized Neural Representations",
author = "Schumacher, Elliot and
Mulyar, Andriy and
Dredze, Mark",
editor = "Jurafsky, Dan and
Chai, Joyce and
Schluter, Natalie and
Tetreault, Joel",
booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
month = jul,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.acl-main.760",
doi = "10.18653/v1/2020.acl-main.760",
pages = "8585--8592",
abstract = "In traditional approaches to entity linking, linking decisions are based on three sources of information {--} the similarity of the mention string to an entity{'}s name, the similarity of the context of the document to the entity, and broader information about the knowledge base (KB). In some domains, there is little contextual information present in the KB and thus we rely more heavily on mention string similarity. We consider one example of this, concept linking, which seeks to link mentions of medical concepts to a medical concept ontology. We propose an approach to concept linking that leverages recent work in contextualized neural models, such as ELMo (Peters et al. 2018), which create a token representation that integrates the surrounding context of the mention and concept name. We find a neural ranking approach paired with contextualized embeddings provides gains over a competitive baseline (Leaman et al. 2013). Additionally, we find that a pre-training step using synonyms from the ontology offers a useful initialization for the ranker.",
}

M. Gordon and K. Duh, “Distill, Adapt, Distill: Training Small, In-Domain Models for Neural Machine Translation,” in Proceedings of the Fourth Workshop on Neural Generation and Translation, Online, 2020, p. 110–118. doi:10.18653/v1/2020.ngt-1.12
[BibTeX] [Abstract] [Link]

We explore best practices for training small, memory efficient machine translation models with sequence-level knowledge distillation in the domain adaptation setting. While both domain adaptation and knowledge distillation are widely-used, their interaction remains little understood. Our large-scale empirical results in machine translation (on three language pairs with three domains each) suggest distilling twice for best performance: once using general-domain data and again using in-domain data with an adapted teacher.

@inproceedings{gordon-duh-2020-distill,
title = "Distill, Adapt, Distill: Training Small, In-Domain Models for Neural Machine Translation",
author = "Gordon, Mitchell and
Duh, Kevin",
editor = "Birch, Alexandra and
Finch, Andrew and
Hayashi, Hiroaki and
Heafield, Kenneth and
Junczys-Dowmunt, Marcin and
Konstas, Ioannis and
Li, Xian and
Neubig, Graham and
Oda, Yusuke",
booktitle = "Proceedings of the Fourth Workshop on Neural Generation and Translation",
month = jul,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.ngt-1.12",
doi = "10.18653/v1/2020.ngt-1.12",
pages = "110--118",
abstract = "We explore best practices for training small, memory efficient machine translation models with sequence-level knowledge distillation in the domain adaptation setting. While both domain adaptation and knowledge distillation are widely-used, their interaction remains little understood. Our large-scale empirical results in machine translation (on three language pairs with three domains each) suggest distilling twice for best performance: once using general-domain data and again using in-domain data with an adapted teacher.",
}

S. Sun, S. Sia, and K. Duh, “CLIReval: Evaluating Machine Translation as a Cross-Lingual Information Retrieval Task,” in Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations, Online, 2020, p. 134–141. doi:10.18653/v1/2020.acl-demos.18
[BibTeX] [Abstract] [Link]

We present CLIReval, an easy-to-use toolkit for evaluating machine translation (MT) with the proxy task of cross-lingual information retrieval (CLIR). Contrary to what the project name might suggest, CLIReval does not actually require any annotated CLIR dataset. Instead, it automatically transforms translations and references used in MT evaluations into a synthetic CLIR dataset; it then sets up a standard search engine (Elasticsearch) and computes various information retrieval metrics (e.g., mean average precision) by treating the translations as documents to be retrieved. The idea is to gauge the quality of MT by its impact on the document translation approach to CLIR. As a case study, we run CLIReval on the {“}metrics shared task{”} of WMT2019; while this extrinsic metric is not intended to replace popular intrinsic metrics such as BLEU, results suggest CLIReval is competitive in many language pairs in terms of correlation to human judgments of quality. CLIReval is publicly available at \url{https://github.com/ssun32/CLIReval}.

@inproceedings{sun-etal-2020-clireval,
title = "{CLIR}eval: Evaluating Machine Translation as a Cross-Lingual Information Retrieval Task",
author = "Sun, Shuo and
Sia, Suzanna and
Duh, Kevin",
editor = "Celikyilmaz, Asli and
Wen, Tsung-Hsien",
booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations",
month = jul,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.acl-demos.18",
doi = "10.18653/v1/2020.acl-demos.18",
pages = "134--141",
abstract = "We present CLIReval, an easy-to-use toolkit for evaluating machine translation (MT) with the proxy task of cross-lingual information retrieval (CLIR). Contrary to what the project name might suggest, CLIReval does not actually require any annotated CLIR dataset. Instead, it automatically transforms translations and references used in MT evaluations into a synthetic CLIR dataset; it then sets up a standard search engine (Elasticsearch) and computes various information retrieval metrics (e.g., mean average precision) by treating the translations as documents to be retrieved. The idea is to gauge the quality of MT by its impact on the document translation approach to CLIR. As a case study, we run CLIReval on the {``}metrics shared task{''} of WMT2019; while this extrinsic metric is not intended to replace popular intrinsic metrics such as BLEU, results suggest CLIReval is competitive in many language pairs in terms of correlation to human judgments of quality. CLIReval is publicly available at \url{https://github.com/ssun32/CLIReval}.",
}

S. Wu and M. Dredze, “Are All Languages Created Equal in Multilingual BERT?,” in Proceedings of the 5th Workshop on Representation Learning for NLP, Online, 2020, p. 120–130. doi:10.18653/v1/2020.repl4nlp-1.16
[BibTeX] [Abstract] [Link]

Multilingual BERT (mBERT) trained on 104 languages has shown surprisingly good cross-lingual performance on several NLP tasks, even without explicit cross-lingual signals. However, these evaluations have focused on cross-lingual transfer with high-resource languages, covering only a third of the languages covered by mBERT. We explore how mBERT performs on a much wider set of languages, focusing on the quality of representation for low-resource languages, measured by within-language performance. We consider three tasks: Named Entity Recognition (99 languages), Part-of-speech Tagging and Dependency Parsing (54 languages each). mBERT does better than or comparable to baselines on high resource languages but does much worse for low resource languages. Furthermore, monolingual BERT models for these languages do even worse. Paired with similar languages, the performance gap between monolingual BERT and mBERT can be narrowed. We find that better models for low resource languages require more efficient pretraining techniques or more data.

@inproceedings{wu-dredze-2020-languages,
title = "Are All Languages Created Equal in Multilingual {BERT}?",
author = "Wu, Shijie and
Dredze, Mark",
editor = "Gella, Spandana and
Welbl, Johannes and
Rei, Marek and
Petroni, Fabio and
Lewis, Patrick and
Strubell, Emma and
Seo, Minjoon and
Hajishirzi, Hannaneh",
booktitle = "Proceedings of the 5th Workshop on Representation Learning for NLP",
month = jul,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.repl4nlp-1.16",
doi = "10.18653/v1/2020.repl4nlp-1.16",
pages = "120--130",
abstract = "Multilingual BERT (mBERT) trained on 104 languages has shown surprisingly good cross-lingual performance on several NLP tasks, even without explicit cross-lingual signals. However, these evaluations have focused on cross-lingual transfer with high-resource languages, covering only a third of the languages covered by mBERT. We explore how mBERT performs on a much wider set of languages, focusing on the quality of representation for low-resource languages, measured by within-language performance. We consider three tasks: Named Entity Recognition (99 languages), Part-of-speech Tagging and Dependency Parsing (54 languages each). mBERT does better than or comparable to baselines on high resource languages but does much worse for low resource languages. Furthermore, monolingual BERT models for these languages do even worse. Paired with similar languages, the performance gap between monolingual BERT and mBERT can be narrowed. We find that better models for low resource languages require more efficient pretraining techniques or more data.",
}

M. Gordon, K. Duh, and N. Andrews, “Compressing BERT: Studying the Effects of Weight Pruning on Transfer Learning,” in Proceedings of the 5th Workshop on Representation Learning for NLP, Online, 2020, p. 143–155. doi:10.18653/v1/2020.repl4nlp-1.18
[BibTeX] [Abstract] [Link]

Pre-trained universal feature extractors, such as BERT for natural language processing and VGG for computer vision, have become effective methods for improving deep learning models without requiring more labeled data. While effective, feature extractors like BERT may be prohibitively large for some deployment scenarios. We explore weight pruning for BERT and ask: how does compression during pre-training affect transfer learning? We find that pruning affects transfer learning in three broad regimes. Low levels of pruning (30-40{\%}) do not affect pre-training loss or transfer to downstream tasks at all. Medium levels of pruning increase the pre-training loss and prevent useful pre-training information from being transferred to downstream tasks. High levels of pruning additionally prevent models from fitting downstream datasets, leading to further degradation. Finally, we observe that fine-tuning BERT on a specific task does not improve its prunability. We conclude that BERT can be pruned once during pre-training rather than separately for each task without affecting performance.

@inproceedings{gordon-etal-2020-compressing,
title = "Compressing {BERT}: Studying the Effects of Weight Pruning on Transfer Learning",
author = "Gordon, Mitchell and
Duh, Kevin and
Andrews, Nicholas",
editor = "Gella, Spandana and
Welbl, Johannes and
Rei, Marek and
Petroni, Fabio and
Lewis, Patrick and
Strubell, Emma and
Seo, Minjoon and
Hajishirzi, Hannaneh",
booktitle = "Proceedings of the 5th Workshop on Representation Learning for NLP",
month = jul,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.repl4nlp-1.18",
doi = "10.18653/v1/2020.repl4nlp-1.18",
pages = "143--155",
abstract = "Pre-trained universal feature extractors, such as BERT for natural language processing and VGG for computer vision, have become effective methods for improving deep learning models without requiring more labeled data. While effective, feature extractors like BERT may be prohibitively large for some deployment scenarios. We explore weight pruning for BERT and ask: how does compression during pre-training affect transfer learning? We find that pruning affects transfer learning in three broad regimes. Low levels of pruning (30-40{\%}) do not affect pre-training loss or transfer to downstream tasks at all. Medium levels of pruning increase the pre-training loss and prevent useful pre-training information from being transferred to downstream tasks. High levels of pruning additionally prevent models from fitting downstream datasets, leading to further degradation. Finally, we observe that fine-tuning BERT on a specific task does not improve its prunability. We conclude that BERT can be pruned once during pre-training rather than separately for each task without affecting performance.",
}

D. Mueller, N. Andrews, and M. Dredze, “Sources of Transfer in Multilingual Named Entity Recognition,” in Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, Online, 2020, p. 8093–8104. doi:10.18653/v1/2020.acl-main.720
[BibTeX] [Abstract] [Link]

Named-entities are inherently multilingual, and annotations in any given language may be limited. This motivates us to consider \textit{polyglot} named-entity recognition (NER), where one model is trained using annotated data drawn from more than one language. However, a straightforward implementation of this simple idea does not always work in practice: naive training of NER models using annotated data drawn from multiple languages consistently underperforms models trained on monolingual data alone, despite having access to more training data. The starting point of this paper is a simple solution to this problem, in which polyglot models are \textit{fine-tuned} on monolingual data to consistently and significantly outperform their monolingual counterparts. To explain this phenomena, we explore the sources of multilingual transfer in polyglot NER models and examine the weight structure of polyglot models compared to their monolingual counterparts. We find that polyglot models efficiently share many parameters across languages and that fine-tuning may utilize a large number of those parameters.

@inproceedings{mueller-etal-2020-sources,
title = "Sources of Transfer in Multilingual Named Entity Recognition",
author = "Mueller, David and
Andrews, Nicholas and
Dredze, Mark",
editor = "Jurafsky, Dan and
Chai, Joyce and
Schluter, Natalie and
Tetreault, Joel",
booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
month = jul,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.acl-main.720",
doi = "10.18653/v1/2020.acl-main.720",
pages = "8093--8104",
abstract = "Named-entities are inherently multilingual, and annotations in any given language may be limited. This motivates us to consider \textit{polyglot} named-entity recognition (NER), where one model is trained using annotated data drawn from more than one language. However, a straightforward implementation of this simple idea does not always work in practice: naive training of NER models using annotated data drawn from multiple languages consistently underperforms models trained on monolingual data alone, despite having access to more training data. The starting point of this paper is a simple solution to this problem, in which polyglot models are \textit{fine-tuned} on monolingual data to consistently and significantly outperform their monolingual counterparts. To explain this phenomena, we explore the sources of multilingual transfer in polyglot NER models and examine the weight structure of polyglot models compared to their monolingual counterparts. We find that polyglot models efficiently share many parameters across languages and that fine-tuning may utilize a large number of those parameters.",
}

H. Mei, G. Qin, M. Xu, and Jason Eisner, “Neural Datalog Through Time: Informed Temporal Modeling via Logical Specification,” in Proceedings of the 37th International Conference on Machine Learning, 2020.
[BibTeX] [Link]

@InProceedings{mei-et-al-2020-icml,
author = "Hongyuan Mei and Guanghui Qin and Minjie Xu and Jason
Eisner",
title = "Neural {D}atalog Through Time: Informed Temporal
Modeling via Logical Specification",
booktitle = "Proceedings of the 37th International Conference on
Machine Learning",
year = "2020",
month = jul,
URL = "http://cs.jhu.edu/~jason/papers/#mei-et-al-2020-icml",
}

E. Salesky, E. Chodroff, Tiago Pimental, M. Wiesner, R. Cotterell, A. W. Black, and J. Eisner, “A Corpus for Large-Scale Phonetic Typology,” in Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL), 2020, p. 2388–2397. doi:10.18653/v1/2020.acl-main.415
[BibTeX] [Link]

@InProceedings{salesky-et-al-2020,
aclid = "2020.acl-main.415",
doi = "10.18653/v1/2020.acl-main.415",
author = "Elizabeth Salesky and Eleanor Chodroff and Tiago
Pimental and Matthew Wiesner and Ryan Cotterell and
Alan W. Black and Jason Eisner",
title = "A Corpus for Large-Scale Phonetic Typology",
booktitle = "Proceedings of the 58th Annual Meeting of the
Association for Computational Linguistics (ACL)",
pages = "2388--2397",
year = "2020",
month = jul,
URL = "http://cs.jhu.edu/~jason/papers/#salesky-et-al-2020",
}

K. Duh, P. McNamee, M. Post, and B. Thompson, “Benchmarking Neural and Statistical Machine Translation on Low-Resource African Languages,” in Proceedings of the Twelfth Language Resources and Evaluation Conference, Marseille, France, 2020, p. 2667–2675.
[BibTeX] [Abstract] [Link]

Research in machine translation (MT) is developing at a rapid pace. However, most work in the community has focused on languages where large amounts of digital resources are available. In this study, we benchmark state of the art statistical and neural machine translation systems on two African languages which do not have large amounts of resources: Somali and Swahili. These languages are of social importance and serve as test-beds for developing technologies that perform reasonably well despite the low-resource constraint. Our findings suggest that statistical machine translation (SMT) and neural machine translation (NMT) can perform similarly in low-resource scenarios, but neural systems require more careful tuning to match performance. We also investigate how to exploit additional data, such as bilingual text harvested from the web, or user dictionaries; we find that NMT can significantly improve in performance with the use of these additional data. Finally, we survey the landscape of machine translation resources for the languages of Africa and provide some suggestions for promising future research directions.

@inproceedings{duh-etal-2020-benchmarking,
title = "Benchmarking Neural and Statistical Machine Translation on Low-Resource {A}frican Languages",
author = "Duh, Kevin and
McNamee, Paul and
Post, Matt and
Thompson, Brian",
editor = "Calzolari, Nicoletta and
B{\'e}chet, Fr{\'e}d{\'e}ric and
Blache, Philippe and
Choukri, Khalid and
Cieri, Christopher and
Declerck, Thierry and
Goggi, Sara and
Isahara, Hitoshi and
Maegaard, Bente and
Mariani, Joseph and
Mazo, H{\'e}l{\`e}ne and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Twelfth Language Resources and Evaluation Conference",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2020.lrec-1.325",
pages = "2667--2675",
abstract = "Research in machine translation (MT) is developing at a rapid pace. However, most work in the community has focused on languages where large amounts of digital resources are available. In this study, we benchmark state of the art statistical and neural machine translation systems on two African languages which do not have large amounts of resources: Somali and Swahili. These languages are of social importance and serve as test-beds for developing technologies that perform reasonably well despite the low-resource constraint. Our findings suggest that statistical machine translation (SMT) and neural machine translation (NMT) can perform similarly in low-resource scenarios, but neural systems require more careful tuning to match performance. We also investigate how to exploit additional data, such as bilingual text harvested from the web, or user dictionaries; we find that NMT can significantly improve in performance with the use of these additional data. Finally, we survey the landscape of machine translation resources for the languages of Africa and provide some suggestions for promising future research directions.",
language = "English",
ISBN = "979-10-95546-34-4",
}

M. Francis-Landau, T. Vieira, and Jason Eisner, “Evaluation of Logic Programs with Built-Ins and Aggregation: A Calculus for Bag Relations,” in 13th International Workshop on Rewriting Logic and Its Applications, 2020, p. 49–63.
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@InProceedings{francislandau-vieira-eisner-2020-wrla,
author = "Matthew Francis-Landau and Tim Vieira and Jason
Eisner",
title = "Evaluation of Logic Programs with Built-Ins and
Aggregation: {A} Calculus for Bag Relations",
booktitle = "13th International Workshop on Rewriting Logic and Its
Applications",
pages = "49--63",
year = "2020",
month = apr,
note = "Extended version (27 pages) available on arXiv,
October 2020.",
URL = "http://cs.jhu.edu/~jason/papers/#francislandau-vieira-eisner-2020-wrla",
}

Hui Ding, Peng Zhou, and R. Chellappa, “Occlusion-Adaptive Deep Network for Robust Facial Expression Recognition,” in 2020 IEEE International Joint Conference on Biometrics (IJCB), 2020.
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@inproceedings{218613798,
title = {Occlusion-Adaptive Deep Network for Robust Facial Expression Recognition},
author = {{Hui Ding} and {Peng Zhou} and {R. Chellappa}},
year = 2020,
month = {5},
booktitle = {2020 IEEE International Joint Conference on Biometrics (IJCB)},
url = {https://www.semanticscholar.org/paper/d7119cbf13386a30e8edbcac93b13aaadb616277},
}

Xuan Zhang and Kevin Duh, “Reproducible and Efficient Benchmarks for Hyperparameter Optimization of Neural Machine Translation Systems,” in Transactions of the Association for Computational Linguistics, 2020.
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title = {Reproducible and Efficient Benchmarks for Hyperparameter Optimization of Neural Machine Translation Systems},
author = {{Xuan Zhang} and {Kevin Duh}},
year = 2020,
month = {7},
booktitle = {Transactions of the Association for Computational Linguistics},
url = {https://www.semanticscholar.org/paper/b91f161bde9756d184f1b5640721e801fa67201e},
}

M. Villemur, P. Julián, Tomas Figliolia, and A. Andreou, “7 TOPS/W Cellular Neural Network Processor Core for Intelligent Internet-of-Things,” in IEEE Transactions on Circuits and Systems – II – Express Briefs, 2020.
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@inproceedings{202095716,
title = {7 TOPS/W Cellular Neural Network Processor Core for Intelligent Internet-of-Things},
author = {{M. Villemur} and {P. Julián} and {Tomas Figliolia} and {A. Andreou}},
year = 2020,
month = {7},
booktitle = {IEEE Transactions on Circuits and Systems - II - Express Briefs},
url = {https://www.semanticscholar.org/paper/3f4a42032803c26ddbbda29a3606ac716f6bf9a6},
}

Jonah P. Sengupta, R. Kubendran, E. Neftci, and A. Andreou, “High-Speed, Real-Time, Spike-Based Object Tracking and Path Prediction on Google Edge TPU,” in International Conference on Artificial Intelligence Circuits and Systems, 2020.
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title = {High-Speed, Real-Time, Spike-Based Object Tracking and Path Prediction on Google Edge TPU},
author = {{Jonah P. Sengupta} and {R. Kubendran} and {E. Neftci} and {A. Andreou}},
year = 2020,
month = {8},
booktitle = {International Conference on Artificial Intelligence Circuits and Systems},
url = {https://www.semanticscholar.org/paper/91a9c098ecb6db93d0aa64b80bbaff1565c4aa75},
}

L. Moro-Velázquez, J. Villalba, and N. Dehak, “Using X-Vectors to Automatically Detect Parkinson’s Disease from Speech,” in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2020.
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title = {Using X-Vectors to Automatically Detect Parkinson’s Disease from Speech},
author = {{L. Moro-Velázquez} and {J. Villalba} and {N. Dehak}},
year = 2020,
month = {5},
booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
url = {https://www.semanticscholar.org/paper/fe52caa985bcf9ad5f2789ddcd1adeaa21a1740e},
}

J. Villalba, Nanxin Chen, David Snyder, D. Garcia-Romero, A. McCree, Gregory Sell, Jonas Borgstrom, Leibny Paola García-Perera, Fred Richardson, Réda Dehak, P. Torres-Carrasquillo, and N. Dehak, “State-of-the-art speaker recognition with neural network embeddings in NIST SRE18 and Speakers in the Wild evaluations,” in Computer Speech and Language, 2020.
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@inproceedings{208098525,
title = {State-of-the-art speaker recognition with neural network embeddings in NIST SRE18 and Speakers in the Wild evaluations},
author = {{J. Villalba} and {Nanxin Chen} and {David Snyder} and {D. Garcia-Romero} and {A. McCree} and {Gregory Sell} and {Jonas Borgstrom} and {Leibny Paola García-Perera} and {Fred Richardson} and {Réda Dehak} and {P. Torres-Carrasquillo} and {N. Dehak}},
year = 2020,
month = {3},
booktitle = {Computer Speech and Language},
url = {https://www.semanticscholar.org/paper/5cdc7e9bd040d11bafc5aa39642b1630bb5ec637},
}

Joseph P. Robinson, Yu Yin, Zaid Khan, Ming Shao, Siyu Xia, Michael Stopa, Samson Timoner, Matthew A. Turk, R. Chellappa, and Y. Fu, “Recognizing Families In the Wild (RFIW): The 4th Edition,” in IEEE International Conference on Automatic Face & Gesture Recognition, 2020.
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@inproceedings{211132726,
title = {Recognizing Families In the Wild (RFIW): The 4th Edition},
author = {{Joseph P. Robinson} and {Yu Yin} and {Zaid Khan} and {Ming Shao} and {Siyu Xia} and {Michael Stopa} and {Samson Timoner} and {Matthew A. Turk} and {R. Chellappa} and {Y. Fu}},
year = 2020,
month = {2},
booktitle = {IEEE International Conference on Automatic Face & Gesture Recognition},
url = {https://www.semanticscholar.org/paper/8a9e437b2e2d813b402ac560c852ef0ab2f1cd3c},
}

Saurabh Kataria, P. S. Nidadavolu, J. Villalba, and N. Dehak, “Analysis of Deep Feature Loss based Enhancement for Speaker Verification,” in The Speaker and Language Recognition Workshop, 2020.
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@inproceedings{211010939,
title = {Analysis of Deep Feature Loss based Enhancement for Speaker Verification},
author = {{Saurabh Kataria} and {P. S. Nidadavolu} and {J. Villalba} and {N. Dehak}},
year = 2020,
month = {2},
booktitle = {The Speaker and Language Recognition Workshop},
url = {https://www.semanticscholar.org/paper/7f505e52f08864af531ea9cdd27ad3fe685a079b},
}

Tomas Figliolia and A. Andreou, “An FPGA multiprocessor architecture for Bayesian online change point detection using stochastic computation,” in Microprocessors and microsystems, 2020.
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@inproceedings{212942489,
title = {An FPGA multiprocessor architecture for Bayesian online change point detection using stochastic computation},
author = {{Tomas Figliolia} and {A. Andreou}},
year = 2020,
month = {4},
booktitle = {Microprocessors and microsystems},
url = {https://www.semanticscholar.org/paper/933aee48d5fdc3cbe7d8097a448e444bb2fb8d7f},
}

M. Naphade, Shuo Wang, D. Anastasiu, Zhenghang Tang, Ming-Ching Chang, Xiaodong Yang, Liang Zheng, Anuj Sharma, R. Chellappa, and Pranamesh Chakraborty, “The 4th AI City Challenge,” in 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2020.
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@inproceedings{260533611,
title = {The 4th AI City Challenge},
author = {{M. Naphade} and {Shuo Wang} and {D. Anastasiu} and {Zhenghang Tang} and {Ming-Ching Chang} and {Xiaodong Yang} and {Liang Zheng} and {Anuj Sharma} and {R. Chellappa} and {Pranamesh Chakraborty}},
year = 2020,
month = {4},
booktitle = {2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
url = {https://www.semanticscholar.org/paper/54d3e211a5c3137ba359731af43d22429608dada},
}

T. Strat, R. Chellappa, and Vishal M. Patel, “Vision and Robotics,” in The AI Magazine, 2020.
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@inproceedings{220687545,
title = {Vision and Robotics},
author = {{T. Strat} and {R. Chellappa} and {Vishal M. Patel}},
year = 2020,
month = {6},
booktitle = {The AI Magazine},
url = {https://www.semanticscholar.org/paper/10c14194c83aec171537e74e4dcb3cfdc24c148e},
}

Zhen Zhang, Chaokun Chang, Haibin Lin, Yida Wang, R. Arora, and Xin Jin, “Is Network the Bottleneck of Distributed Training?,” in NetAI@SIGCOMM, 2020.
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@inproceedings{219793032,
title = {Is Network the Bottleneck of Distributed Training?},
author = {{Zhen Zhang} and {Chaokun Chang} and {Haibin Lin} and {Yida Wang} and {R. Arora} and {Xin Jin}},
year = 2020,
month = {6},
booktitle = {NetAI@SIGCOMM},
url = {https://www.semanticscholar.org/paper/cfa6e7ac8bef5b3aadcdc7a27d2a9e9d508b3322},
}

Cheng Peng, Wei-An Lin, Haofu Liao, R. Chellappa, and S. Zhou, “SAINT: Spatially Aware Interpolation NeTwork for Medical Slice Synthesis,” in Computer Vision and Pattern Recognition, 2020.
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@inproceedings{209832256,
title = {SAINT: Spatially Aware Interpolation NeTwork for Medical Slice Synthesis},
author = {{Cheng Peng} and {Wei-An Lin} and {Haofu Liao} and {R. Chellappa} and {S. Zhou}},
year = 2020,
month = {1},
booktitle = {Computer Vision and Pattern Recognition},
url = {https://www.semanticscholar.org/paper/cfbfee77c684bc5fa73ab7519f10f0b5ff5a82f5},
}

Paiheng Xu, Mark Dredze, and David A. Broniatowski, “The Twitter Social Mobility Index: Measuring Social Distancing Practices from Geolocated Tweets,” in arXiv.org, 2020.
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@inproceedings{214802296,
title = {The Twitter Social Mobility Index: Measuring Social Distancing Practices from Geolocated Tweets},
author = {{Paiheng Xu} and {Mark Dredze} and {David A. Broniatowski}},
year = 2020,
month = {4},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/1d52942c836fe3e32f0fe5748f4c137fceea50a6},
}

Ankan Bansal, Rajeev Ranjan, C. Castillo, and R. Chellappa, “Deep CNN-Based Face Recognition,” in Computer Vision, 2020.
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@inproceedings{215931996,
title = {Deep CNN-Based Face Recognition},
author = {{Ankan Bansal} and {Rajeev Ranjan} and {C. Castillo} and {R. Chellappa}},
year = 2020,
booktitle = {Computer Vision},
url = {https://www.semanticscholar.org/paper/d98e495f03f2daabb65dfeb32de54e1cd8e3be30},
}

Shuo Sun and Kevin Duh, “Modeling Document Interactions for Learning to Rank with Regularized Self-Attention,” in arXiv.org, 2020.
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@inproceedings{218571136,
title = {Modeling Document Interactions for Learning to Rank with Regularized Self-Attention},
author = {{Shuo Sun} and {Kevin Duh}},
year = 2020,
month = {5},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/152e3a33dce17fe5d003be2267765df638b8ebd4},
}

B. Bosworth, Iskandar Atakhodjaev, M. Kossey, Brian C. Grubel, Daniel S. Vresilovic, J. R. Stroud, Neil Macfarlane, J. Villalba, N. Dehak, A. B. Cooper, Mark A. Foster, and A. Foster, “Unclonable photonic keys hardened against machine learning attacks.” 2020.
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@inproceedings{214257492,
title = {Unclonable photonic keys hardened against machine learning attacks},
author = {{B. Bosworth} and {Iskandar Atakhodjaev} and {M. Kossey} and {Brian C. Grubel} and {Daniel S. Vresilovic} and {J. R. Stroud} and {Neil Macfarlane} and {J. Villalba} and {N. Dehak} and {A. B. Cooper} and {Mark A. Foster} and {A. Foster}},
year = 2020,
month = {1},
booktitle = {},
url = {https://www.semanticscholar.org/paper/13e94fa0bd9b5bbb7528431603feaeec3682b427},
}

T. Shinozaki, Shinji Watanabe, and Kevin Duh, “Automated Development of DNN Based Spoken Language Systems Using Evolutionary Algorithms,” in Deep Neural Evolution, 2020.
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@inproceedings{219451512,
title = {Automated Development of DNN Based Spoken Language Systems Using Evolutionary Algorithms},
author = {{T. Shinozaki} and {Shinji Watanabe} and {Kevin Duh}},
year = 2020,
booktitle = {Deep Neural Evolution},
url = {https://www.semanticscholar.org/paper/f2e544c5333125ee30c1c34b08936b6ef87c97dd},
}

Piotr Żelasko, Laureano Moro-Vel’azquez, M. Hasegawa-Johnson, O. Scharenborg, and N. Dehak, “That Sounds Familiar: an Analysis of Phonetic Representations Transfer Across Languages,” in Interspeech, 2020.
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@inproceedings{218674480,
title = {That Sounds Familiar: an Analysis of Phonetic Representations Transfer Across Languages},
author = {{Piotr Żelasko} and {Laureano Moro-Vel'azquez} and {M. Hasegawa-Johnson} and {O. Scharenborg} and {N. Dehak}},
year = 2020,
month = {5},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/b10e212e462b48f21cc8d8a2ee23487ead0edf50},
}

Theodore L. Caputi, J. Ayers, Mark Dredze, Nicholas Suplina, and S. Burd-Sharps, “Collateral Crises of Gun Preparation and the COVID-19 Pandemic: Infodemiology Study,” in JMIR Public Health and Surveillance, 2020.
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@inproceedings{218833257,
title = {Collateral Crises of Gun Preparation and the COVID-19 Pandemic: Infodemiology Study},
author = {{Theodore L. Caputi} and {J. Ayers} and {Mark Dredze} and {Nicholas Suplina} and {S. Burd-Sharps}},
year = 2020,
month = {4},
booktitle = {JMIR Public Health and Surveillance},
url = {https://www.semanticscholar.org/paper/71f262238a9210fc2af72a8f06ce5a09a6b4fb3f},
}

R. Pappagari, Tianzi Wang, J. Villalba, Nanxin Chen, and N. Dehak, “X-Vectors Meet Emotions: A Study On Dependencies Between Emotion and Speaker Recognition,” in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2020.
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@inproceedings{211083028,
title = {X-Vectors Meet Emotions: A Study On Dependencies Between Emotion and Speaker Recognition},
author = {{R. Pappagari} and {Tianzi Wang} and {J. Villalba} and {Nanxin Chen} and {N. Dehak}},
year = 2020,
month = {2},
booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
url = {https://www.semanticscholar.org/paper/1441844ecd0e0dc33a4edf3eb48f0b06de9293ec},
}

Prithviraj Dhar, Joshua Gleason, Hossein Souri, C. Castillo, and R. Chellappa, “Towards Gender-Neutral Face Descriptors for Mitigating Bias in Face Recognition,” in arXiv: Computer Vision and Pattern Recognition, 2020.
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title = {Towards Gender-Neutral Face Descriptors for Mitigating Bias in Face Recognition},
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year = 2020,
month = {6},
booktitle = {arXiv: Computer Vision and Pattern Recognition},
url = {https://www.semanticscholar.org/paper/1bd2fba7083829042d0ba0765dbed8ec692cb335},
}

Saurabhchand Bhati, J. Villalba, Piotr Żelasko, and N. Dehak, “Self-Expressing Autoencoders for Unsupervised Spoken Term Discovery,” in Interspeech, 2020.
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@inproceedings{220793482,
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author = {{Saurabhchand Bhati} and {J. Villalba} and {Piotr Żelasko} and {N. Dehak}},
year = 2020,
month = {7},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/c92a826a96b59848bbca5e6c2710b97b54435262},
}

Xiaolei Huang, Amelia M. Jamison, David A. Broniatowski, S. Quinn, and Mark Dredze, “Coronavirus Twitter Data: A collection of COVID-19 tweets with automated annotations.” 2020.
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title = {Coronavirus Twitter Data: A collection of COVID-19 tweets with automated annotations},
author = {{Xiaolei Huang} and {Amelia M. Jamison} and {David A. Broniatowski} and {S. Quinn} and {Mark Dredze}},
year = 2020,
month = {3},
booktitle = {},
url = {https://www.semanticscholar.org/paper/97e9c9c03b5208538083e6ebc1b49768145c899f},
}

Michael Liu, Theodore L. Caputi, Mark Dredze, A. Kesselheim, and J. Ayers, “Internet Searches for Unproven COVID-19 Therapies in the United States.,” in JAMA Internal Medicine, 2020.
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author = {{Michael Liu} and {Theodore L. Caputi} and {Mark Dredze} and {A. Kesselheim} and {J. Ayers}},
year = 2020,
month = {4},
booktitle = {JAMA Internal Medicine},
url = {https://www.semanticscholar.org/paper/4838dc8eef22add083218846480835f94e60647a},
}

Jingxiao Zheng and R. Chellappa, “Video-Based Face Recognition,” in Computer Vision, 2020.
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@inproceedings{33992699,
title = {Video-Based Face Recognition},
author = {{Jingxiao Zheng} and {R. Chellappa}},
year = 2020,
booktitle = {Computer Vision},
url = {https://www.semanticscholar.org/paper/2b02743e2372c17d8026e1e093507a554e75908d},
}

R. Arora, T. V. Marinov, and M. Mohri, “Corralling Stochastic Bandit Algorithms,” in International Conference on Artificial Intelligence and Statistics, 2020.
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title = {Corralling Stochastic Bandit Algorithms},
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month = {6},
booktitle = {International Conference on Artificial Intelligence and Statistics},
url = {https://www.semanticscholar.org/paper/e083fb44158c21824c1da9d0cf89dc157fd18ab4},
}

Lukasz Augustyniak, Piotr Szymański, Mikolaj Morzy, Piotr Żelasko, Adrian Szymczak, Jan Mizgajski, Yishay Carmiel, and N. Dehak, “Punctuation Prediction in Spontaneous Conversations: Can We Mitigate ASR Errors with Retrofitted Word Embeddings?,” in Interspeech, 2020.
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@inproceedings{215745684,
title = {Punctuation Prediction in Spontaneous Conversations: Can We Mitigate ASR Errors with Retrofitted Word Embeddings?},
author = {{Lukasz Augustyniak} and {Piotr Szymański} and {Mikolaj Morzy} and {Piotr Żelasko} and {Adrian Szymczak} and {Jan Mizgajski} and {Yishay Carmiel} and {N. Dehak}},
year = 2020,
month = {4},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/60411edec172bcfa7b0f27ceff54bf5546e10cbe},
}

P. S. Nidadavolu, Saurabh Kataria, Leibny Paola García-Perera, J. Villalba, and N. Dehak, “Single Channel Far Field Feature Enhancement For Speaker Verification In The Wild,” in arXiv.org, 2020.
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@inproceedings{218674572,
title = {Single Channel Far Field Feature Enhancement For Speaker Verification In The Wild},
author = {{P. S. Nidadavolu} and {Saurabh Kataria} and {Leibny Paola García-Perera} and {J. Villalba} and {N. Dehak}},
year = 2020,
month = {5},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/f1f072d88905a9d52cd759dd16ab42f2eedf4908},
}

Pirazh Khorramshahi, Neehar Peri, Jun-Cheng Chen, and R. Chellappa, “The Devil is in the Details: Self-Supervised Attention for Vehicle Re-Identification,” in European Conference on Computer Vision, 2020.
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title = {The Devil is in the Details: Self-Supervised Attention for Vehicle Re-Identification},
author = {{Pirazh Khorramshahi} and {Neehar Peri} and {Jun-Cheng Chen} and {R. Chellappa}},
year = 2020,
month = {4},
booktitle = {European Conference on Computer Vision},
url = {https://www.semanticscholar.org/paper/7bba8759784a0d982362d73834784b02fe62d536},
}

R. Arora, T. V. Marinov, and Enayat Ullah, “Private Stochastic Convex Optimization: Efficient Algorithms for Non-smooth Objectives,” in arXiv.org, 2020.
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title = {Private Stochastic Convex Optimization: Efficient Algorithms for Non-smooth Objectives},
author = {{R. Arora} and {T. V. Marinov} and {Enayat Ullah}},
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month = {2},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/bbe5973d9ee5a5301bfbd3e0fcdc086ef694229e},
}

L. Moro-Velázquez and N. Dehak, “A Review of the Use of Prosodic Aspects of Speech for the Automatic Detection and Assessment of Parkinson’s Disease.” 2020.
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@inproceedings{234972697,
title = {A Review of the Use of Prosodic Aspects of Speech for the Automatic Detection and Assessment of Parkinson’s Disease},
author = {{L. Moro-Velázquez} and {N. Dehak}},
year = 2020,
booktitle = {},
url = {https://www.semanticscholar.org/paper/062cd4c2f467638f91c9a2903a28179308b558ba},
}

R. Arora, P. Bartlett, Poorya Mianjy, and N. Srebro, “Dropout: Explicit Forms and Capacity Control,” in International Conference on Machine Learning, 2020.
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year = 2020,
month = {3},
booktitle = {International Conference on Machine Learning},
url = {https://www.semanticscholar.org/paper/404c8ec7d40d58b8ea6bc634262101486cb74300},
}

J. Ayers, E. Leas, Derek C. Johnson, Adam Poliak, B. Althouse, Mark Dredze, and A. Nobles, “Internet Searches for Acute Anxiety During the Early Stages of the COVID-19 Pandemic.,” in JAMA Internal Medicine, 2020.
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@inproceedings{221279230,
title = {Internet Searches for Acute Anxiety During the Early Stages of the COVID-19 Pandemic.},
author = {{J. Ayers} and {E. Leas} and {Derek C. Johnson} and {Adam Poliak} and {B. Althouse} and {Mark Dredze} and {A. Nobles}},
year = 2020,
month = {8},
booktitle = {JAMA Internal Medicine},
url = {https://www.semanticscholar.org/paper/e40f55267e05aef6026cc3c449d5c69b11429ced},
}

Paiheng Xu, Mark Dredze, and David A. Broniatowski, “The Twitter Social Mobility Index: Measuring Social Distancing Practices With Geolocated Tweets,” in Journal of Medical Internet Research, 2020.
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@inproceedings{222352548,
title = {The Twitter Social Mobility Index: Measuring Social Distancing Practices With Geolocated Tweets},
author = {{Paiheng Xu} and {Mark Dredze} and {David A. Broniatowski}},
year = 2020,
month = {6},
booktitle = {Journal of Medical Internet Research},
url = {https://www.semanticscholar.org/paper/48214dc2d0e5d13f9e2127d4149e154a3dcfd3aa},
}

Ankan Bansal, Sai Saketh Rambhatla, Abhinav Shrivastava, and R. Chellappa, “Spatial Priming for Detecting Human-Object Interactions,” in arXiv.org, 2020.
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@inproceedings{215737036,
title = {Spatial Priming for Detecting Human-Object Interactions},
author = {{Ankan Bansal} and {Sai Saketh Rambhatla} and {Abhinav Shrivastava} and {R. Chellappa}},
year = 2020,
month = {4},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/61c9cb51312aa890a3ad1f3a4f53ae048ecaa216},
}

David A. Broniatowski, S. Quinn, Mark Dredze, and Amelia M. Jamison, “Vaccine Communication as Weaponized Identity Politics.,” in American Journal of Public Health, 2020.
[BibTeX] [Link]

@inproceedings{215605318,
title = {Vaccine Communication as Weaponized Identity Politics.},
author = {{David A. Broniatowski} and {S. Quinn} and {Mark Dredze} and {Amelia M. Jamison}},
year = 2020,
month = {4},
booktitle = {American Journal of Public Health},
url = {https://www.semanticscholar.org/paper/8cb0984b67d823f705168f47a86f53b7037f7602},
}

Ankan Bansal, Yuting Zhang, and R. Chellappa, “Visual Question Answering on Image Sets,” in European Conference on Computer Vision, 2020.
[BibTeX] [Link]

@inproceedings{221340919,
title = {Visual Question Answering on Image Sets},
author = {{Ankan Bansal} and {Yuting Zhang} and {R. Chellappa}},
year = 2020,
month = {8},
booktitle = {European Conference on Computer Vision},
url = {https://www.semanticscholar.org/paper/18ba4e542a5206a40e308f54ceffc6786b7d94d2},
}

Laureano Moro-Veláquez, Estefanía Hernández-García, J. Gómez-García, Juan Ignacio Godino-Llorente, and N. Dehak, “Analysis of the Effects of Supraglottal Tract Surgical Procedures in Automatic Speaker Recognition Performance,” in IEEE/ACM Transactions on Audio Speech and Language Processing, 2020.
[BibTeX] [Link]

@inproceedings{211057197,
title = {Analysis of the Effects of Supraglottal Tract Surgical Procedures in Automatic Speaker Recognition Performance},
author = {{Laureano Moro-Veláquez} and {Estefanía Hernández-García} and {J. Gómez-García} and {Juan Ignacio Godino-Llorente} and {N. Dehak}},
year = 2020,
month = {1},
booktitle = {IEEE/ACM Transactions on Audio Speech and Language Processing},
url = {https://www.semanticscholar.org/paper/f79edadd9328510165201638d214b0c71ab95f8c},
}

Juan Ignacio Godino-Llorente, D. O’Shaughnessy, Tan Lee, N. Dehak, and C. Manfredi, “Introduction to the Issue on Automatic Assessment of Health Disorders Based on Voice, Speech, and Language Processing,” in IEEE Journal on Selected Topics in Signal Processing, 2020.
[BibTeX] [Link]

@inproceedings{216347423,
title = {Introduction to the Issue on Automatic Assessment of Health Disorders Based on Voice, Speech, and Language Processing},
author = {{Juan Ignacio Godino-Llorente} and {D. O'Shaughnessy} and {Tan Lee} and {N. Dehak} and {C. Manfredi}},
year = 2020,
month = {2},
booktitle = {IEEE Journal on Selected Topics in Signal Processing},
url = {https://www.semanticscholar.org/paper/a5f03e768619b91fccbc3c4c038e1fb21a38bd7f},
}

Dian Hu, Christine Martin, Mark Dredze, and David A. Broniatowski, “Chinese social media suggest decreased vaccine acceptance in China: An observational study on Weibo following the 2018 Changchun Changsheng vaccine incident.,” in Vaccine, 2020.
[BibTeX] [Link]

@inproceedings{211475802,
title = {Chinese social media suggest decreased vaccine acceptance in China: An observational study on Weibo following the 2018 Changchun Changsheng vaccine incident.},
author = {{Dian Hu} and {Christine Martin} and {Mark Dredze} and {David A. Broniatowski}},
year = 2020,
month = {2},
booktitle = {Vaccine},
url = {https://www.semanticscholar.org/paper/fb86f4a86bb16ab7c6fa151d9355eedb397706a7},
}

Xiaodong Liu, Kevin Duh, Liyuan Liu, and Jianfeng Gao, “Very Deep Transformers for Neural Machine Translation,” in arXiv.org, 2020.
[BibTeX] [Link]

@inproceedings{221150462,
title = {Very Deep Transformers for Neural Machine Translation},
author = {{Xiaodong Liu} and {Kevin Duh} and {Liyuan Liu} and {Jianfeng Gao}},
year = 2020,
month = {8},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/81909b3ca71f0d828797922e1c36e018efae1759},
}

Zach Wood-Doughty, I. Shpitser, and Mark Dredze, “Sensitivity Analyses for Incorporating Machine Learning Predictions into Causal Estimates.” 2020.
[BibTeX] [Link]

@inproceedings{237248742,
title = {Sensitivity Analyses for Incorporating Machine Learning Predictions into Causal Estimates},
author = {{Zach Wood-Doughty} and {I. Shpitser} and {Mark Dredze}},
year = 2020,
booktitle = {},
url = {https://www.semanticscholar.org/paper/1b15fec2ec2be09069c7ee836b165e687fc90e5a},
}

Juan Ignacio Godino-Llorente, L. Moro-Velázquez, J. Gómez-García, Jeung-Yoon Choi, N. Dehak, and S. Shattuck-Hufnagel, “Approaches to Evaluate Parkinsonian Speech Using Artificial Models.” 2020.
[BibTeX] [Link]

@inproceedings{235033790,
title = {Approaches to Evaluate Parkinsonian Speech Using Artificial Models},
author = {{Juan Ignacio Godino-Llorente} and {L. Moro-Velázquez} and {J. Gómez-García} and {Jeung-Yoon Choi} and {N. Dehak} and {S. Shattuck-Hufnagel}},
year = 2020,
booktitle = {},
url = {https://www.semanticscholar.org/paper/e093ab0150e2ed5b1568c6a9868ef18b6e69d7e0},
}

Boyu Lu, Jun-Cheng Chen, and R. Chellappa, “UID-GAN: Unsupervised Image Deblurring via Disentangled Representations,” in IEEE Transactions on Biometrics Behavior and Identity Science, 2020.
[BibTeX] [Link]

@inproceedings{210972040,
title = {UID-GAN: Unsupervised Image Deblurring via Disentangled Representations},
author = {{Boyu Lu} and {Jun-Cheng Chen} and {R. Chellappa}},
year = 2020,
month = {1},
booktitle = {IEEE Transactions on Biometrics Behavior and Identity Science},
url = {https://www.semanticscholar.org/paper/1ede4513462dcd8aad056d7fc420302f9f1dfc40},
}

Prithviraj Dhar, Joshua Gleason, Hossein Souri, C. Castillo, and R. Chellappa, “An adversarial learning algorithm for mitigating gender bias in face recognition,” in arXiv.org, 2020.
[BibTeX] [Link]

@inproceedings{219687846,
title = {An adversarial learning algorithm for mitigating gender bias in face recognition},
author = {{Prithviraj Dhar} and {Joshua Gleason} and {Hossein Souri} and {C. Castillo} and {R. Chellappa}},
year = 2020,
month = {6},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/31a07feb4acedbb1854dcc06befce5fbfc27c24b},
}

L. Moro-Velázquez, J. Gómez-García, Juan Ignacio Godino-Llorente, F. Grandas-Perez, S. Shattuck-Hufnagel, V. Yagüe-Jiménez, and N. Dehak, “Phonetic relevance and phonemic grouping of speech in the automatic detection of Parkinson’s Disease,” in Scientific Reports, 2019.
[BibTeX] [Link]

@inproceedings{209331418,
title = {Phonetic relevance and phonemic grouping of speech in the automatic detection of Parkinson’s Disease},
author = {{L. Moro-Velázquez} and {J. Gómez-García} and {Juan Ignacio Godino-Llorente} and {F. Grandas-Perez} and {S. Shattuck-Hufnagel} and {V. Yagüe-Jiménez} and {N. Dehak}},
year = 2019,
month = {12},
booktitle = {Scientific Reports},
url = {https://www.semanticscholar.org/paper/bc4156658cd9330fb18dfdb577e5913a7f7878c3},
}

Mitchell A. Gordon and Kevin Duh, “Explaining Sequence-Level Knowledge Distillation as Data-Augmentation for Neural Machine Translation,” in arXiv.org, 2019.
[BibTeX] [Link]

@inproceedings{208910258,
title = {Explaining Sequence-Level Knowledge Distillation as Data-Augmentation for Neural Machine Translation},
author = {{Mitchell A. Gordon} and {Kevin Duh}},
year = 2019,
month = {12},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/d1ba8c532b954ea8b3a66d9c155e769fc2081af6},
}

Nils Holzenberger and R. Arora, “Multiview Representation Learning for a Union of Subspaces,” in arXiv.org, 2019.
[BibTeX] [Link]

@inproceedings{209515968,
title = {Multiview Representation Learning for a Union of Subspaces},
author = {{Nils Holzenberger} and {R. Arora}},
year = 2019,
month = {12},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/68941236b9ea941350180427fe60aa1f3644ae75},
}

Ilya Kavalerov, W. Czaja, and R. Chellappa, “cGANs with Multi-Hinge Loss,” in arXiv.org, 2019.
[BibTeX] [Link]

@inproceedings{208910107,
title = {cGANs with Multi-Hinge Loss},
author = {{Ilya Kavalerov} and {W. Czaja} and {R. Chellappa}},
year = 2019,
month = {12},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/c1d58def0becaeaf368e124f2898ccd89f0c74eb},
}

Leibny Paola García-Perera, J. Villalba, H. Bredin, Jun Du, Diego Castán, Alejandrina Cristia, Latané Bullock, Ling Guo, K. Okabe, P. S. Nidadavolu, Saurabh Kataria, Sizhu Chen, Léo Galmant, Marvin Lavechin, Lei Sun, Marie-Philippe Gill, Bar Ben-Yair, Sajjad Abdoli, Xin Wang, Wassim Bouaziz, Hadrien Titeux, Emmanuel Dupoux, Kong Aik LEE, and N. Dehak, “Speaker detection in the wild: Lessons learned from JSALT 2019,” in The Speaker and Language Recognition Workshop, 2019.
[BibTeX] [Link]

@inproceedings{208527071,
title = {Speaker detection in the wild: Lessons learned from JSALT 2019},
author = {{Leibny Paola García-Perera} and {J. Villalba} and {H. Bredin} and {Jun Du} and {Diego Castán} and {Alejandrina Cristia} and {Latané Bullock} and {Ling Guo} and {K. Okabe} and {P. S. Nidadavolu} and {Saurabh Kataria} and {Sizhu Chen} and {Léo Galmant} and {Marvin Lavechin} and {Lei Sun} and {Marie-Philippe Gill} and {Bar Ben-Yair} and {Sajjad Abdoli} and {Xin Wang} and {Wassim Bouaziz} and {Hadrien Titeux} and {Emmanuel Dupoux} and {Kong Aik LEE} and {N. Dehak}},
year = 2019,
month = {12},
booktitle = {The Speaker and Language Recognition Workshop},
url = {https://www.semanticscholar.org/paper/6876fe4afb24da70b886e881431e0273394ad865},
}

Saurabhchand Bhati, L. Moro-Velázquez, J. Villalba, and N. Dehak, “LSTM Siamese Network for Parkinson’s Disease Detection from Speech,” in IEEE Global Conference on Signal and Information Processing, 2019.
[BibTeX] [Link]

@inproceedings{210971728,
title = {LSTM Siamese Network for Parkinson’s Disease Detection from Speech},
author = {{Saurabhchand Bhati} and {L. Moro-Velázquez} and {J. Villalba} and {N. Dehak}},
year = 2019,
month = {11},
booktitle = {IEEE Global Conference on Signal and Information Processing},
url = {https://www.semanticscholar.org/paper/e8c28555fe828a27a691a24608cd229c0359c8b1},
}

Amelia M. Jamison, David A. Broniatowski, Mark Dredze, Zach Wood-Doughty, DureAden Khan, and S. Quinn, “Vaccine-related advertising in the Facebook Ad Archive.,” in Vaccine, 2019.
[BibTeX] [Link]

@inproceedings{208063342,
title = {Vaccine-related advertising in the Facebook Ad Archive.},
author = {{Amelia M. Jamison} and {David A. Broniatowski} and {Mark Dredze} and {Zach Wood-Doughty} and {DureAden Khan} and {S. Quinn}},
year = 2019,
month = {11},
booktitle = {Vaccine},
url = {https://www.semanticscholar.org/paper/09d933efcaaaeedec22d08bceb09dc2b3e7b7efd},
}

S. Zhang, X. Ma, K. Duh, and B. Van Durme, “Broad-Coverage Semantic Parsing as Transduction,” in Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), Hong Kong, China, 2019, p. 3786–3798. doi:10.18653/v1/D19-1392
[BibTeX] [Abstract] [Link]

We unify different broad-coverage semantic parsing tasks into a transduction parsing paradigm, and propose an attention-based neural transducer that incrementally builds meaning representation via a sequence of semantic relations. By leveraging multiple attention mechanisms, the neural transducer can be effectively trained without relying on a pre-trained aligner. Experiments separately conducted on three broad-coverage semantic parsing tasks {–} AMR, SDP and UCCA {–} demonstrate that our attention-based neural transducer improves the state of the art on both AMR and UCCA, and is competitive with the state of the art on SDP.

@inproceedings{zhang-etal-2019-broad,
title = "Broad-Coverage Semantic Parsing as Transduction",
author = "Zhang, Sheng and
Ma, Xutai and
Duh, Kevin and
Van Durme, Benjamin",
editor = "Inui, Kentaro and
Jiang, Jing and
Ng, Vincent and
Wan, Xiaojun",
booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)",
month = nov,
year = "2019",
address = "Hong Kong, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D19-1392",
doi = "10.18653/v1/D19-1392",
pages = "3786--3798",
abstract = "We unify different broad-coverage semantic parsing tasks into a transduction parsing paradigm, and propose an attention-based neural transducer that incrementally builds meaning representation via a sequence of semantic relations. By leveraging multiple attention mechanisms, the neural transducer can be effectively trained without relying on a pre-trained aligner. Experiments separately conducted on three broad-coverage semantic parsing tasks {--} AMR, SDP and UCCA {--} demonstrate that our attention-based neural transducer improves the state of the art on both AMR and UCCA, and is competitive with the state of the art on SDP.",
}

A. Nobles, E. Leas, B. Althouse, Mark Dredze, C. Longhurst, Davey M. Smith, and J. Ayers, “Requests for Diagnoses of Sexually Transmitted Diseases on a Social Media Platform.,” in Journal of the American Medical Association (JAMA), 2019.
[BibTeX] [Link]

@inproceedings{207894590,
title = {Requests for Diagnoses of Sexually Transmitted Diseases on a Social Media Platform.},
author = {{A. Nobles} and {E. Leas} and {B. Althouse} and {Mark Dredze} and {C. Longhurst} and {Davey M. Smith} and {J. Ayers}},
year = 2019,
month = {11},
booktitle = {Journal of the American Medical Association (JAMA)},
url = {https://www.semanticscholar.org/paper/9d98c236bf7e729db2b31cace3328e335dc8a942},
}

Elliot Schumacher and Mark Dredze, “Learning unsupervised contextual representations for medical synonym discovery,” in JAMIA Open, 2019.
[BibTeX] [Link]

@inproceedings{211033454,
title = {Learning unsupervised contextual representations for medical synonym discovery},
author = {{Elliot Schumacher} and {Mark Dredze}},
year = 2019,
month = {11},
booktitle = {JAMIA Open},
url = {https://www.semanticscholar.org/paper/cad8a6b9248227d041f35acbfb341ab870d8995f},
}

S. Wu and M. Dredze, “Beto, Bentz, Becas: The Surprising Cross-Lingual Effectiveness of BERT,” in Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), Hong Kong, China, 2019, p. 833–844. doi:10.18653/v1/D19-1077
[BibTeX] [Abstract] [Link]

Pretrained contextual representation models (Peters et al., 2018; Devlin et al., 2018) have pushed forward the state-of-the-art on many NLP tasks. A new release of BERT (Devlin, 2018) includes a model simultaneously pretrained on 104 languages with impressive performance for zero-shot cross-lingual transfer on a natural language inference task. This paper explores the broader cross-lingual potential of mBERT (multilingual) as a zero shot language transfer model on 5 NLP tasks covering a total of 39 languages from various language families: NLI, document classification, NER, POS tagging, and dependency parsing. We compare mBERT with the best-published methods for zero-shot cross-lingual transfer and find mBERT competitive on each task. Additionally, we investigate the most effective strategy for utilizing mBERT in this manner, determine to what extent mBERT generalizes away from language specific features, and measure factors that influence cross-lingual transfer.

@inproceedings{wu-dredze-2019-beto,
title = "Beto, Bentz, Becas: The Surprising Cross-Lingual Effectiveness of {BERT}",
author = "Wu, Shijie and
Dredze, Mark",
editor = "Inui, Kentaro and
Jiang, Jing and
Ng, Vincent and
Wan, Xiaojun",
booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)",
month = nov,
year = "2019",
address = "Hong Kong, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D19-1077",
doi = "10.18653/v1/D19-1077",
pages = "833--844",
abstract = "Pretrained contextual representation models (Peters et al., 2018; Devlin et al., 2018) have pushed forward the state-of-the-art on many NLP tasks. A new release of BERT (Devlin, 2018) includes a model simultaneously pretrained on 104 languages with impressive performance for zero-shot cross-lingual transfer on a natural language inference task. This paper explores the broader cross-lingual potential of mBERT (multilingual) as a zero shot language transfer model on 5 NLP tasks covering a total of 39 languages from various language families: NLI, document classification, NER, POS tagging, and dependency parsing. We compare mBERT with the best-published methods for zero-shot cross-lingual transfer and find mBERT competitive on each task. Additionally, we investigate the most effective strategy for utilizing mBERT in this manner, determine to what extent mBERT generalizes away from language specific features, and measure factors that influence cross-lingual transfer.",
}

Nanxin Chen, Shinji Watanabe, J. Villalba, and N. Dehak, “Listen and Fill in the Missing Letters: Non-Autoregressive Transformer for Speech Recognition,” in arXiv.org, 2019.
[BibTeX] [Link]

@inproceedings{214802613,
title = {Listen and Fill in the Missing Letters: Non-Autoregressive Transformer for Speech Recognition},
author = {{Nanxin Chen} and {Shinji Watanabe} and {J. Villalba} and {N. Dehak}},
year = 2019,
month = {11},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/2de8019fd7d04e3d1305d5efaeeb591f0d966550},
}

Wei-An Lin, Y. Balaji, Pouya Samangouei, and R. Chellappa, “Invert and Defend: Model-based Approximate Inversion of Generative Adversarial Networks for Secure Inference,” in arXiv.org, 2019.
[BibTeX] [Link]

@inproceedings{208268082,
title = {Invert and Defend: Model-based Approximate Inversion of Generative Adversarial Networks for Secure Inference},
author = {{Wei-An Lin} and {Y. Balaji} and {Pouya Samangouei} and {R. Chellappa}},
year = 2019,
month = {11},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/34adff99c6ce47057b24c1bd1305adf292403fa7},
}

B. Thompson, R. Knowles, X. Zhang, H. Khayrallah, K. Duh, and P. Koehn, “HABLex: Human Annotated Bilingual Lexicons for Experiments in Machine Translation,” in Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), Hong Kong, China, 2019, p. 1382–1387. doi:10.18653/v1/D19-1142
[BibTeX] [Abstract] [Link]

Bilingual lexicons are valuable resources used by professional human translators. While these resources can be easily incorporated in statistical machine translation, it is unclear how to best do so in the neural framework. In this work, we present the HABLex dataset, designed to test methods for bilingual lexicon integration into neural machine translation. Our data consists of human generated alignments of words and phrases in machine translation test sets in three language pairs (Russian-English, Chinese-English, and Korean-English), resulting in clean bilingual lexicons which are well matched to the reference. We also present two simple baselines – constrained decoding and continued training – and an improvement to continued training to address overfitting.

@inproceedings{thompson-etal-2019-hablex,
title = "{HABL}ex: Human Annotated Bilingual Lexicons for Experiments in Machine Translation",
author = "Thompson, Brian and
Knowles, Rebecca and
Zhang, Xuan and
Khayrallah, Huda and
Duh, Kevin and
Koehn, Philipp",
editor = "Inui, Kentaro and
Jiang, Jing and
Ng, Vincent and
Wan, Xiaojun",
booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)",
month = nov,
year = "2019",
address = "Hong Kong, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D19-1142",
doi = "10.18653/v1/D19-1142",
pages = "1382--1387",
abstract = "Bilingual lexicons are valuable resources used by professional human translators. While these resources can be easily incorporated in statistical machine translation, it is unclear how to best do so in the neural framework. In this work, we present the HABLex dataset, designed to test methods for bilingual lexicon integration into neural machine translation. Our data consists of human generated alignments of words and phrases in machine translation test sets in three language pairs (Russian-English, Chinese-English, and Korean-English), resulting in clean bilingual lexicons which are well matched to the reference. We also present two simple baselines - constrained decoding and continued training - and an improvement to continued training to address overfitting.",
}

Nanxin Chen, Shinji Watanabe, J. Villalba, and N. Dehak, “Non-Autoregressive Transformer Automatic Speech Recognition,” in arXiv: Audio and Speech Processing, 2019.
[BibTeX] [Link]

@inproceedings{207863618,
title = {Non-Autoregressive Transformer Automatic Speech Recognition},
author = {{Nanxin Chen} and {Shinji Watanabe} and {J. Villalba} and {N. Dehak}},
year = 2019,
month = {11},
booktitle = {arXiv: Audio and Speech Processing},
url = {https://www.semanticscholar.org/paper/49f657d704a1b80ce3dba0d8a9e5479ec1d703d4},
}

Saurabhchand Bhati, Chunxi Liu, J. Villalba, J. Trmal, S. Khudanpur, and N. Dehak, “Bottom-Up Unsupervised Word Discovery via Acoustic Units,” in IEEE Global Conference on Signal and Information Processing, 2019.
[BibTeX] [Link]

@inproceedings{210972323,
title = {Bottom-Up Unsupervised Word Discovery via Acoustic Units},
author = {{Saurabhchand Bhati} and {Chunxi Liu} and {J. Villalba} and {J. Trmal} and {S. Khudanpur} and {N. Dehak}},
year = 2019,
month = {11},
booktitle = {IEEE Global Conference on Signal and Information Processing},
url = {https://www.semanticscholar.org/paper/2a626d33a9e7af638eac1660426a486288a489cc},
}

X. L. Li and J. Eisner, “Specializing Word Embeddings (for Parsing) by Information Bottleneck,” in Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, Hong Kong, 2019, p. 2744–2754. doi:10.18653/v1/D19-1276
[BibTeX] [Link]

@InProceedings{li-eisner-2019,
aclid = "D19-1276",
doi = "10.18653/v1/D19-1276",
author = "Xiang Lisa Li and Jason Eisner",
title = "Specializing Word Embeddings (for Parsing) by
Information Bottleneck",
booktitle = "Proceedings of the 2019 Conference on Empirical
Methods in Natural Language Processing and 9th
International Joint Conference on Natural Language
Processing",
pages = "2744--2754",
year = "2019",
month = nov,
address = "Hong Kong",
note = "Best Paper Award.",
URL = "http://cs.jhu.edu/~jason/papers/#li-eisner-2019",
}

A. Renduchintala, P. Koehn, and Jason Eisner, “Spelling-Aware Construction of Macaronic Texts for Teaching Foreign-Language Vocabulary,” in Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, Hong Kong, 2019, p. 6439–6444. doi:10.18653/v1/D19-1679
[BibTeX] [Link]

@InProceedings{renduchintala-et-al-2019-emnlp,
aclid = "D19-1679",
doi = "10.18653/v1/D19-1679",
author = "Adithya Renduchintala and Philipp Koehn and Jason
Eisner",
title = "Spelling-Aware Construction of Macaronic Texts for
Teaching Foreign-Language Vocabulary",
booktitle = "Proceedings of the 2019 Conference on Empirical
Methods in Natural Language Processing and 9th
International Joint Conference on Natural Language
Processing",
pages = "6439--6444",
year = "2019",
month = nov,
address = "Hong Kong",
URL = "http://cs.jhu.edu/~jason/papers/#renduchintala-et-al-2019-emnlp",
}

Alycen Wiacek, Eduardo A. Gonzalez, N. Dehak, and M. L. Lediju Bell, “CohereNet: A deep learning approach to coherence-based beamforming,” in IUS, 2019.
[BibTeX] [Link]

@inproceedings{209320431,
title = {CohereNet: A deep learning approach to coherence-based beamforming},
author = {{Alycen Wiacek} and {Eduardo A. Gonzalez} and {N. Dehak} and {M. L. Lediju Bell}},
year = 2019,
month = {10},
booktitle = {IUS},
url = {https://www.semanticscholar.org/paper/02eac7f9a573c7b2852235733bf8d1920ce788ee},
}

P. S. Nidadavolu, Saurabh Kataria, J. Villalba, Leibny Paola García-Perera, and N. Dehak, “Unsupervised Feature Enhancement for Speaker Verification,” in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2019.
[BibTeX] [Link]

@inproceedings{204907138,
title = {Unsupervised Feature Enhancement for Speaker Verification},
author = {{P. S. Nidadavolu} and {Saurabh Kataria} and {J. Villalba} and {Leibny Paola García-Perera} and {N. Dehak}},
year = 2019,
month = {10},
booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
url = {https://www.semanticscholar.org/paper/df49e860305c871f5078bf7aa0b8cef7dcda11e7},
}

Li Liu, M. Pietikäinen, Jie Chen, Guoying Zhao, Xiaogang Wang, and R. Chellappa, “Guest Editors’ Introduction to the Special Section on Compact and Efficient Feature Representation and Learning in Computer Vision,” in IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019.
[BibTeX] [Link]

@inproceedings{202550367,
title = {Guest Editors' Introduction to the Special Section on Compact and Efficient Feature Representation and Learning in Computer Vision},
author = {{Li Liu} and {M. Pietikäinen} and {Jie Chen} and {Guoying Zhao} and {Xiaogang Wang} and {R. Chellappa}},
year = 2019,
month = {10},
booktitle = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
url = {https://www.semanticscholar.org/paper/3c0f6d2b76c9d68da37e319cdae9802298ca7c44},
}

Maneet Singh, M. Chawla, Richa Singh, Mayank Vatsa, and R. Chellappa, “Disguised Faces in the Wild 2019,” in 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), 2019.
[BibTeX] [Link]

@inproceedings{207901958,
title = {Disguised Faces in the Wild 2019},
author = {{Maneet Singh} and {M. Chawla} and {Richa Singh} and {Mayank Vatsa} and {R. Chellappa}},
year = 2019,
month = {10},
booktitle = {2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)},
url = {https://www.semanticscholar.org/paper/65e62791fc8df7d578991937533e41d5c4dc5263},
}

H. Inaguma, Kevin Duh, Tatsuya Kawahara, and Shinji Watanabe, “Multilingual End-to-End Speech Translation,” in Automatic Speech Recognition & Understanding, 2019.
[BibTeX] [Link]

@inproceedings{203610481,
title = {Multilingual End-to-End Speech Translation},
author = {{H. Inaguma} and {Kevin Duh} and {Tatsuya Kawahara} and {Shinji Watanabe}},
year = 2019,
month = {10},
booktitle = {Automatic Speech Recognition & Understanding},
url = {https://www.semanticscholar.org/paper/8b231737e0048a400527d89aa56c712e8b9bc690},
}

R. Pappagari, Piotr Żelasko, J. Villalba, Yishay Carmiel, and N. Dehak, “Hierarchical Transformers for Long Document Classification,” in Automatic Speech Recognition & Understanding, 2019.
[BibTeX] [Link]

@inproceedings{204852089,
title = {Hierarchical Transformers for Long Document Classification},
author = {{R. Pappagari} and {Piotr Żelasko} and {J. Villalba} and {Yishay Carmiel} and {N. Dehak}},
year = 2019,
month = {10},
booktitle = {Automatic Speech Recognition & Understanding},
url = {https://www.semanticscholar.org/paper/46b3ba0f3cb8340bc94f26e0fdf6dc4e38f68948},
}

E. Leas, A. Nobles, Theodore L. Caputi, Mark Dredze, Davey M. Smith, and J. Ayers, “Trends in Internet Searches for Cannabidiol (CBD) in the United States,” in JAMA Network Open, 2019.
[BibTeX] [Link]

@inproceedings{204848948,
title = {Trends in Internet Searches for Cannabidiol (CBD) in the United States},
author = {{E. Leas} and {A. Nobles} and {Theodore L. Caputi} and {Mark Dredze} and {Davey M. Smith} and {J. Ayers}},
year = 2019,
month = {10},
booktitle = {JAMA Network Open},
url = {https://www.semanticscholar.org/paper/30672fad20fa70024c7311140b7e702b8201974c},
}

P. S. Nidadavolu, Saurabh Kataria, J. Villalba, and N. Dehak, “Low-Resource Domain Adaptation for Speaker Recognition Using Cycle-Gans,” in Automatic Speech Recognition & Understanding, 2019.
[BibTeX] [Link]

@inproceedings{204976547,
title = {Low-Resource Domain Adaptation for Speaker Recognition Using Cycle-Gans},
author = {{P. S. Nidadavolu} and {Saurabh Kataria} and {J. Villalba} and {N. Dehak}},
year = 2019,
month = {10},
booktitle = {Automatic Speech Recognition & Understanding},
url = {https://www.semanticscholar.org/paper/373acc04096d80a03dba238f73ce96930a3abb7b},
}

Prithviraj Dhar, Ankan Bansal, C. Castillo, Joshua Gleason, P. Phillips, and R. Chellappa, “How are attributes expressed in face DCNNs?,” in IEEE International Conference on Automatic Face & Gesture Recognition, 2019.
[BibTeX] [Link]

@inproceedings{204509539,
title = {How are attributes expressed in face DCNNs?},
author = {{Prithviraj Dhar} and {Ankan Bansal} and {C. Castillo} and {Joshua Gleason} and {P. Phillips} and {R. Chellappa}},
year = 2019,
month = {10},
booktitle = {IEEE International Conference on Automatic Face & Gesture Recognition},
url = {https://www.semanticscholar.org/paper/73587f97500203b94a9f312b0b86891f62326679},
}

Saurabh Kataria, P. S. Nidadavolu, J. Villalba, Nanxin Chen, Paola García, and N. Dehak, “Feature Enhancement with Deep Feature Losses for Speaker Verification,” in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2019.
[BibTeX] [Link]

@inproceedings{204976531,
title = {Feature Enhancement with Deep Feature Losses for Speaker Verification},
author = {{Saurabh Kataria} and {P. S. Nidadavolu} and {J. Villalba} and {Nanxin Chen} and {Paola García} and {N. Dehak}},
year = 2019,
month = {10},
booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
url = {https://www.semanticscholar.org/paper/343fa6aea1bf71751f632be85fde936c66d21356},
}

Andriy Mulyar, Elliot Schumacher, Masoud Rouhizadeh, and Mark Dredze, “Phenotyping of Clinical Notes with Improved Document Classification Models Using Contextualized Neural Language Models,” in arXiv.org, 2019.
[BibTeX] [Link]

@inproceedings{204961310,
title = {Phenotyping of Clinical Notes with Improved Document Classification Models Using Contextualized Neural Language Models},
author = {{Andriy Mulyar} and {Elliot Schumacher} and {Masoud Rouhizadeh} and {Mark Dredze}},
year = 2019,
month = {10},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/c975d19e3861621b287a05bba31f6e1e3f0c4285},
}

Arthita Ghosh and R. Chellappa, “Single-Shot 3D Mesh Estimation via Adversarial Domain Adaptation,” in SN Computer Science, 2019.
[BibTeX] [Link]

@inproceedings{204539408,
title = {Single-Shot 3D Mesh Estimation via Adversarial Domain Adaptation},
author = {{Arthita Ghosh} and {R. Chellappa}},
year = 2019,
month = {10},
booktitle = {SN Computer Science},
url = {https://www.semanticscholar.org/paper/b80646f9b8d51090dfe383575680b00a268410a4},
}

Chun Pong Lau, Hossein Souri, and R. Chellappa, “ATFaceGAN: Single Face Image Restoration and Recognition from Atmospheric Turbulence,” in IEEE International Conference on Automatic Face & Gesture Recognition, 2019.
[BibTeX] [Link]

@inproceedings{203902626,
title = {ATFaceGAN: Single Face Image Restoration and Recognition from Atmospheric Turbulence},
author = {{Chun Pong Lau} and {Hossein Souri} and {R. Chellappa}},
year = 2019,
month = {10},
booktitle = {IEEE International Conference on Automatic Face & Gesture Recognition},
url = {https://www.semanticscholar.org/paper/57fea03ab1b4e3d06fae5770a01875e7143118fa},
}

M. Martindale, M. Carpuat, K. Duh, and P. McNamee, “Identifying Fluently Inadequate Output in Neural and Statistical Machine Translation,” in Proceedings of Machine Translation Summit XVII: Research Track, Dublin, Ireland, 2019, p. 233–243.
[BibTeX] [Link]

@inproceedings{martindale-etal-2019-identifying,
title = "Identifying Fluently Inadequate Output in Neural and Statistical Machine Translation",
author = "Martindale, Marianna and
Carpuat, Marine and
Duh, Kevin and
McNamee, Paul",
editor = "Forcada, Mikel and
Way, Andy and
Haddow, Barry and
Sennrich, Rico",
booktitle = "Proceedings of Machine Translation Summit XVII: Research Track",
month = aug,
year = "2019",
address = "Dublin, Ireland",
publisher = "European Association for Machine Translation",
url = "https://aclanthology.org/W19-6623",
pages = "233--243",
}

S. Ding, A. Renduchintala, and K. Duh, “A Call for Prudent Choice of Subword Merge Operations in Neural Machine Translation,” in Proceedings of Machine Translation Summit XVII: Research Track, Dublin, Ireland, 2019, p. 204–213.
[BibTeX] [Link]

@inproceedings{ding-etal-2019-call,
title = "A Call for Prudent Choice of Subword Merge Operations in Neural Machine Translation",
author = "Ding, Shuoyang and
Renduchintala, Adithya and
Duh, Kevin",
editor = "Forcada, Mikel and
Way, Andy and
Haddow, Barry and
Sennrich, Rico",
booktitle = "Proceedings of Machine Translation Summit XVII: Research Track",
month = aug,
year = "2019",
address = "Dublin, Ireland",
publisher = "European Association for Machine Translation",
url = "https://aclanthology.org/W19-6620",
pages = "204--213",
}

T. Lippincott, P. Shapiro, K. Duh, and P. McNamee, “JHU System Description for the MADAR Arabic Dialect Identification Shared Task,” in Proceedings of the Fourth Arabic Natural Language Processing Workshop, Florence, Italy, 2019, p. 264–268. doi:10.18653/v1/W19-4634
[BibTeX] [Abstract] [Link]

Our submission to the MADAR shared task on Arabic dialect identification employed a language modeling technique called Prediction by Partial Matching, an ensemble of neural architectures, and sources of additional data for training word embeddings and auxiliary language models. We found several of these techniques provided small boosts in performance, though a simple character-level language model was a strong baseline, and a lower-order LM achieved best performance on Subtask 2. Interestingly, word embeddings provided no consistent benefit, and ensembling struggled to outperform the best component submodel. This suggests the variety of architectures are learning redundant information, and future work may focus on encouraging decorrelated learning.

@inproceedings{lippincott-etal-2019-jhu,
title = "{JHU} System Description for the {MADAR} {A}rabic Dialect Identification Shared Task",
author = "Lippincott, Tom and
Shapiro, Pamela and
Duh, Kevin and
McNamee, Paul",
editor = "El-Hajj, Wassim and
Belguith, Lamia Hadrich and
Bougares, Fethi and
Magdy, Walid and
Zitouni, Imed and
Tomeh, Nadi and
El-Haj, Mahmoud and
Zaghouani, Wajdi",
booktitle = "Proceedings of the Fourth Arabic Natural Language Processing Workshop",
month = aug,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W19-4634",
doi = "10.18653/v1/W19-4634",
pages = "264--268",
abstract = "Our submission to the MADAR shared task on Arabic dialect identification employed a language modeling technique called Prediction by Partial Matching, an ensemble of neural architectures, and sources of additional data for training word embeddings and auxiliary language models. We found several of these techniques provided small boosts in performance, though a simple character-level language model was a strong baseline, and a lower-order LM achieved best performance on Subtask 2. Interestingly, word embeddings provided no consistent benefit, and ensembling struggled to outperform the best component submodel. This suggests the variety of architectures are learning redundant information, and future work may focus on encouraging decorrelated learning.",
}

M. Yarmohammadi, X. Ma, S. Hisamoto, M. Rahman, Y. Wang, H. Xu, D. Povey, P. Koehn, and K. Duh, “Robust Document Representations for Cross-Lingual Information Retrieval in Low-Resource Settings,” in Proceedings of Machine Translation Summit XVII: Research Track, Dublin, Ireland, 2019, p. 12–20.
[BibTeX] [Link]

@inproceedings{yarmohammadi-etal-2019-robust,
title = "Robust Document Representations for Cross-Lingual Information Retrieval in Low-Resource Settings",
author = "Yarmohammadi, Mahsa and
Ma, Xutai and
Hisamoto, Sorami and
Rahman, Muhammad and
Wang, Yiming and
Xu, Hainan and
Povey, Daniel and
Koehn, Philipp and
Duh, Kevin",
editor = "Forcada, Mikel and
Way, Andy and
Haddow, Barry and
Sennrich, Rico",
booktitle = "Proceedings of Machine Translation Summit XVII: Research Track",
month = aug,
year = "2019",
address = "Dublin, Ireland",
publisher = "European Association for Machine Translation",
url = "https://aclanthology.org/W19-6602",
pages = "12--20",
}

M. Post and K. Duh, “JHU 2019 Robustness Task System Description,” in Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1), Florence, Italy, 2019, p. 552–558. doi:10.18653/v1/W19-5366
[BibTeX] [Abstract] [Link]

We describe the JHU submissions to the French{–}English, Japanese{–}English, and English{–}Japanese Robustness Task at WMT 2019. Our goal was to evaluate the performance of baseline systems on both the official noisy test set as well as news data, in order to ensure that performance gains in the latter did not come at the expense of general-domain performance. To this end, we built straightforward 6-layer Transformer models and experimented with a handful of variables including subword processing (FRâEN) and a handful of hyperparameters settings (JAâEN). As expected, our systems performed reasonably.

@inproceedings{post-duh-2019-jhu,
title = "{JHU} 2019 Robustness Task System Description",
author = "Post, Matt and
Duh, Kevin",
editor = "Bojar, Ond{\v{r}}ej and
Chatterjee, Rajen and
Federmann, Christian and
Fishel, Mark and
Graham, Yvette and
Haddow, Barry and
Huck, Matthias and
Yepes, Antonio Jimeno and
Koehn, Philipp and
Martins, Andr{\'e} and
Monz, Christof and
Negri, Matteo and
N{\'e}v{\'e}ol, Aur{\'e}lie and
Neves, Mariana and
Post, Matt and
Turchi, Marco and
Verspoor, Karin",
booktitle = "Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1)",
month = aug,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W19-5366",
doi = "10.18653/v1/W19-5366",
pages = "552--558",
abstract = "We describe the JHU submissions to the French{--}English, Japanese{--}English, and English{--}Japanese Robustness Task at WMT 2019. Our goal was to evaluate the performance of baseline systems on both the official noisy test set as well as news data, in order to ensure that performance gains in the latter did not come at the expense of general-domain performance. To this end, we built straightforward 6-layer Transformer models and experimented with a handful of variables including subword processing (FRâEN) and a handful of hyperparameters settings (JAâEN). As expected, our systems performed reasonably.",
}

A. Renduchintala, P. Shapiro, K. Duh, and P. Koehn, “Character-Aware Decoder for Translation into Morphologically Rich Languages,” in Proceedings of Machine Translation Summit XVII: Research Track, Dublin, Ireland, 2019, p. 244–255.
[BibTeX] [Link]

@inproceedings{renduchintala-etal-2019-character,
title = "Character-Aware Decoder for Translation into Morphologically Rich Languages",
author = "Renduchintala, Adithya and
Shapiro, Pamela and
Duh, Kevin and
Koehn, Philipp",
editor = "Forcada, Mikel and
Way, Andy and
Haddow, Barry and
Sennrich, Rico",
booktitle = "Proceedings of Machine Translation Summit XVII: Research Track",
month = aug,
year = "2019",
address = "Dublin, Ireland",
publisher = "European Association for Machine Translation",
url = "https://aclanthology.org/W19-6624",
pages = "244--255",
}

A. Benton, H. Khayrallah, B. Gujral, D. A. Reisinger, S. Zhang, and R. Arora, “Deep Generalized Canonical Correlation Analysis,” in Proceedings of the 4th Workshop on Representation Learning for NLP (RepL4NLP-2019), Florence, Italy, 2019, p. 1–6. doi:10.18653/v1/W19-4301
[BibTeX] [Abstract] [Link]

We present Deep Generalized Canonical Correlation Analysis (DGCCA) {–} a method for learning nonlinear transformations of arbitrarily many views of data, such that the resulting transformations are maximally informative of each other. While methods for nonlinear two view representation learning (Deep CCA, (Andrew et al., 2013)) and linear many-view representation learning (Generalized CCA (Horst, 1961)) exist, DGCCA combines the flexibility of nonlinear (deep) representation learning with the statistical power of incorporating information from many sources, or views. We present the DGCCA formulation as well as an efficient stochastic optimization algorithm for solving it. We learn and evaluate DGCCA representations for three downstream tasks: phonetic transcription from acoustic {&} articulatory measurements, recommending hashtags and recommending friends on a dataset of Twitter users.

@inproceedings{benton-etal-2019-deep,
title = "Deep Generalized Canonical Correlation Analysis",
author = "Benton, Adrian and
Khayrallah, Huda and
Gujral, Biman and
Reisinger, Dee Ann and
Zhang, Sheng and
Arora, Raman",
editor = "Augenstein, Isabelle and
Gella, Spandana and
Ruder, Sebastian and
Kann, Katharina and
Can, Burcu and
Welbl, Johannes and
Conneau, Alexis and
Ren, Xiang and
Rei, Marek",
booktitle = "Proceedings of the 4th Workshop on Representation Learning for NLP (RepL4NLP-2019)",
month = aug,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W19-4301",
doi = "10.18653/v1/W19-4301",
pages = "1--6",
abstract = "We present Deep Generalized Canonical Correlation Analysis (DGCCA) {--} a method for learning nonlinear transformations of arbitrarily many views of data, such that the resulting transformations are maximally informative of each other. While methods for nonlinear two view representation learning (Deep CCA, (Andrew et al., 2013)) and linear many-view representation learning (Generalized CCA (Horst, 1961)) exist, DGCCA combines the flexibility of nonlinear (deep) representation learning with the statistical power of incorporating information from many sources, or views. We present the DGCCA formulation as well as an efficient stochastic optimization algorithm for solving it. We learn and evaluate DGCCA representations for three downstream tasks: phonetic transcription from acoustic {\&} articulatory measurements, recommending hashtags and recommending friends on a dataset of Twitter users.",
}

A. Renduchintala, P. Koehn, and Jason Eisner, “Simple Construction of Mixed-Language Texts for Vocabulary Learning,” in Proceedings of the 14th Workshop on Innovative Use of NLP for Building Educational Applications (BEA), Florence, 2019, p. 369–379. doi:10.18653/v1/W19-4439
[BibTeX] [Link]

@InProceedings{renduchintala-et-al-2019-bea,
aclid = "W19-4439",
doi = "10.18653/v1/W19-4439",
author = "Adithya Renduchintala and Philipp Koehn and Jason
Eisner",
title = "Simple Construction of Mixed-Language Texts for
Vocabulary Learning",
booktitle = "Proceedings of the 14th Workshop on Innovative Use of
NLP for Building Educational Applications (BEA)",
pages = "369--379",
year = "2019",
month = aug,
address = "Florence",
URL = "http://cs.jhu.edu/~jason/papers/#renduchintala-et-al-2019-bea",
}

S. Zhang, X. Ma, K. Duh, and B. Van Durme, “AMR Parsing as Sequence-to-Graph Transduction,” in Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, Florence, Italy, 2019, p. 80–94. doi:10.18653/v1/P19-1009
[BibTeX] [Abstract] [Link]

We propose an attention-based model that treats AMR parsing as sequence-to-graph transduction. Unlike most AMR parsers that rely on pre-trained aligners, external semantic resources, or data augmentation, our proposed parser is aligner-free, and it can be effectively trained with limited amounts of labeled AMR data. Our experimental results outperform all previously reported SMATCH scores, on both AMR 2.0 (76.3{\%} on LDC2017T10) and AMR 1.0 (70.2{\%} on LDC2014T12).

@inproceedings{zhang-etal-2019-amr,
title = "{AMR} Parsing as Sequence-to-Graph Transduction",
author = "Zhang, Sheng and
Ma, Xutai and
Duh, Kevin and
Van Durme, Benjamin",
editor = "Korhonen, Anna and
Traum, David and
M{\`a}rquez, Llu{\'\i}s",
booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics",
month = jul,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P19-1009",
doi = "10.18653/v1/P19-1009",
pages = "80--94",
abstract = "We propose an attention-based model that treats AMR parsing as sequence-to-graph transduction. Unlike most AMR parsers that rely on pre-trained aligners, external semantic resources, or data augmentation, our proposed parser is aligner-free, and it can be effectively trained with limited amounts of labeled AMR data. Our experimental results outperform all previously reported SMATCH scores, on both AMR 2.0 (76.3{\%} on LDC2017T10) and AMR 1.0 (70.2{\%} on LDC2014T12).",
}

S. J. Mielke, R. Cotterell, K. Gorman, B. Roark, and J. Eisner, “What Kind of Language Is Hard to Language-Model?,” in Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL), Florence, 2019, p. 4975–4989. doi:10.18653/v1/P19-1491
[BibTeX] [Link]

@InProceedings{mielke-et-al-2019,
aclid = "P19-1491",
doi = "10.18653/v1/P19-1491",
author = "Sabrina J. Mielke and Ryan Cotterell and Kyle Gorman
and Brian Roark and Jason Eisner",
title = "What Kind of Language Is Hard to Language-Model?",
booktitle = "Proceedings of the 57th Annual Meeting of the
Association for Computational Linguistics (ACL)",
pages = "4975--4989",
year = "2019",
month = jul,
address = "Florence",
URL = "http://cs.jhu.edu/~jason/papers/#mielke-et-al-2019",
}

B. Thompson, J. Gwinnup, H. Khayrallah, K. Duh, and P. Koehn, “Overcoming Catastrophic Forgetting During Domain Adaptation of Neural Machine Translation,” in Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), Minneapolis, Minnesota, 2019, p. 2062–2068. doi:10.18653/v1/N19-1209
[BibTeX] [Abstract] [Link]

Continued training is an effective method for domain adaptation in neural machine translation. However, in-domain gains from adaptation come at the expense of general-domain performance. In this work, we interpret the drop in general-domain performance as catastrophic forgetting of general-domain knowledge. To mitigate it, we adapt Elastic Weight Consolidation (EWC){–-}a machine learning method for learning a new task without forgetting previous tasks. Our method retains the majority of general-domain performance lost in continued training without degrading in-domain performance, outperforming the previous state-of-the-art. We also explore the full range of general-domain performance available when some in-domain degradation is acceptable.

@inproceedings{thompson-etal-2019-overcoming,
title = "Overcoming Catastrophic Forgetting During Domain Adaptation of Neural Machine Translation",
author = "Thompson, Brian and
Gwinnup, Jeremy and
Khayrallah, Huda and
Duh, Kevin and
Koehn, Philipp",
editor = "Burstein, Jill and
Doran, Christy and
Solorio, Thamar",
booktitle = "Proceedings of the 2019 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)",
month = jun,
year = "2019",
address = "Minneapolis, Minnesota",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N19-1209",
doi = "10.18653/v1/N19-1209",
pages = "2062--2068",
abstract = "Continued training is an effective method for domain adaptation in neural machine translation. However, in-domain gains from adaptation come at the expense of general-domain performance. In this work, we interpret the drop in general-domain performance as catastrophic forgetting of general-domain knowledge. To mitigate it, we adapt Elastic Weight Consolidation (EWC){---}a machine learning method for learning a new task without forgetting previous tasks. Our method retains the majority of general-domain performance lost in continued training without degrading in-domain performance, outperforming the previous state-of-the-art. We also explore the full range of general-domain performance available when some in-domain degradation is acceptable.",
}

S. Amir, M. Dredze, and J. W. Ayers, “Mental Health Surveillance over Social Media with Digital Cohorts,” in Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology, Minneapolis, Minnesota, 2019, p. 114–120. doi:10.18653/v1/W19-3013
[BibTeX] [Abstract] [Link]

The ability to track mental health conditions via social media opened the doors for large-scale, automated, mental health surveillance. However, inferring accurate population-level trends requires representative samples of the underlying population, which can be challenging given the biases inherent in social media data. While previous work has adjusted samples based on demographic estimates, the populations were selected based on specific outcomes, e.g. specific mental health conditions. We depart from these methods, by conducting analyses over demographically representative digital cohorts of social media users. To validated this approach, we constructed a cohort of US based Twitter users to measure the prevalence of depression and PTSD, and investigate how these illnesses manifest across demographic subpopulations. The analysis demonstrates that cohort-based studies can help control for sampling biases, contextualize outcomes, and provide deeper insights into the data.

@inproceedings{amir-etal-2019-mental,
title = "Mental Health Surveillance over Social Media with Digital Cohorts",
author = "Amir, Silvio and
Dredze, Mark and
Ayers, John W.",
editor = "Niederhoffer, Kate and
Hollingshead, Kristy and
Resnik, Philip and
Resnik, Rebecca and
Loveys, Kate",
booktitle = "Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology",
month = jun,
year = "2019",
address = "Minneapolis, Minnesota",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W19-3013",
doi = "10.18653/v1/W19-3013",
pages = "114--120",
abstract = "The ability to track mental health conditions via social media opened the doors for large-scale, automated, mental health surveillance. However, inferring accurate population-level trends requires representative samples of the underlying population, which can be challenging given the biases inherent in social media data. While previous work has adjusted samples based on demographic estimates, the populations were selected based on specific outcomes, e.g. specific mental health conditions. We depart from these methods, by conducting analyses over demographically representative digital cohorts of social media users. To validated this approach, we constructed a cohort of US based Twitter users to measure the prevalence of depression and PTSD, and investigate how these illnesses manifest across demographic subpopulations. The analysis demonstrates that cohort-based studies can help control for sampling biases, contextualize outcomes, and provide deeper insights into the data.",
}

P. Shapiro and K. Duh, “Comparing Pipelined and Integrated Approaches to Dialectal Arabic Neural Machine Translation,” in Proceedings of the Sixth Workshop on NLP for Similar Languages, Varieties and Dialects, Ann Arbor, Michigan, 2019, p. 214–222. doi:10.18653/v1/W19-1424
[BibTeX] [Abstract] [Link]

When translating diglossic languages such as Arabic, situations may arise where we would like to translate a text but do not know which dialect it is. A traditional approach to this problem is to design dialect identification systems and dialect-specific machine translation systems. However, under the recent paradigm of neural machine translation, shared multi-dialectal systems have become a natural alternative. Here we explore under which conditions it is beneficial to perform dialect identification for Arabic neural machine translation versus using a general system for all dialects.

@inproceedings{shapiro-duh-2019-comparing,
title = "Comparing Pipelined and Integrated Approaches to Dialectal {A}rabic Neural Machine Translation",
author = "Shapiro, Pamela and
Duh, Kevin",
editor = {Zampieri, Marcos and
Nakov, Preslav and
Malmasi, Shervin and
Ljube{\v{s}}i{\'c}, Nikola and
Tiedemann, J{\"o}rg and
Ali, Ahmed},
booktitle = "Proceedings of the Sixth Workshop on {NLP} for Similar Languages, Varieties and Dialects",
month = jun,
year = "2019",
address = "Ann Arbor, Michigan",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W19-1424",
doi = "10.18653/v1/W19-1424",
pages = "214--222",
abstract = "When translating diglossic languages such as Arabic, situations may arise where we would like to translate a text but do not know which dialect it is. A traditional approach to this problem is to design dialect identification systems and dialect-specific machine translation systems. However, under the recent paradigm of neural machine translation, shared multi-dialectal systems have become a natural alternative. Here we explore under which conditions it is beneficial to perform dialect identification for Arabic neural machine translation versus using a general system for all dialects.",
}

X. Zhang, P. Shapiro, G. Kumar, P. McNamee, M. Carpuat, and K. Duh, “Curriculum Learning for Domain Adaptation in Neural Machine Translation,” in Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), Minneapolis, Minnesota, 2019, p. 1903–1915. doi:10.18653/v1/N19-1189
[BibTeX] [Abstract] [Link]

We introduce a curriculum learning approach to adapt generic neural machine translation models to a specific domain. Samples are grouped by their similarities to the domain of interest and each group is fed to the training algorithm with a particular schedule. This approach is simple to implement on top of any neural framework or architecture, and consistently outperforms both unadapted and adapted baselines in experiments with two distinct domains and two language pairs.

@inproceedings{zhang-etal-2019-curriculum,
title = "Curriculum Learning for Domain Adaptation in Neural Machine Translation",
author = "Zhang, Xuan and
Shapiro, Pamela and
Kumar, Gaurav and
McNamee, Paul and
Carpuat, Marine and
Duh, Kevin",
editor = "Burstein, Jill and
Doran, Christy and
Solorio, Thamar",
booktitle = "Proceedings of the 2019 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)",
month = jun,
year = "2019",
address = "Minneapolis, Minnesota",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N19-1189",
doi = "10.18653/v1/N19-1189",
pages = "1903--1915",
abstract = "We introduce a curriculum learning approach to adapt generic neural machine translation models to a specific domain. Samples are grouped by their similarities to the domain of interest and each group is fed to the training algorithm with a particular schedule. This approach is simple to implement on top of any neural framework or architecture, and consistently outperforms both unadapted and adapted baselines in experiments with two distinct domains and two language pairs.",
}

H. Mei, G. Qin, and J. Eisner, “Imputing Missing Events in Continuous-Time Event Streams,” in Proceedings of the 36th International Conference on Machine Learning, Long Beach, California, 2019.
[BibTeX] [Link]

@InProceedings{mei-et-al-2019,
author = "Hongyuan Mei and Guanghui Qin and Jason Eisner",
title = "Imputing Missing Events in Continuous-Time Event
Streams",
booktitle = "Proceedings of the 36th International Conference on
Machine Learning",
year = "2019",
month = jun,
address = "Long Beach, California",
URL = "http://cs.jhu.edu/~jason/papers/#mei-et-al-2019",
}

C. Lin, H. Zhu, M. Gormley, and J. Eisner, “Neural Finite-State Transducers: Beyond Rational Relations,” in Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT), Minneapolis, 2019, p. 272–283. doi:10.18653/v1/N19-1024
[BibTeX] [Link]

@InProceedings{lin-et-al-2019,
aclid = "N19-1024",
doi = "10.18653/v1/N19-1024",
author = "Chu-Cheng Lin and Hao Zhu and Matthew Gormley and
Jason Eisner",
title = "Neural Finite-State Transducers: Beyond Rational
Relations",
booktitle = "Proceedings of the 2019 Conference of the North
American Chapter of the Association for Computational
Linguistics: Human Language Technologies (NAACL-HLT)",
pages = "272--283",
year = "2019",
month = jun,
address = "Minneapolis",
URL = "http://cs.jhu.edu/~jason/papers/#lin-et-al-2019",
}

E. Vylomova, R. Cotterell, T. Baldwin, T. Cohn, and J. Eisner, “Contextualization of Morphological Inflection,” in Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT), Minneapolis, 2019, p. 2018–2024. doi:10.18653/v1/N19-1203
[BibTeX] [Link]

@InProceedings{vylomova-et-al-2019,
aclid = "N19-1203",
doi = "10.18653/v1/N19-1203",
author = "Ekaterina Vylomova and Ryan Cotterell and Tim Baldwin
and Trevor Cohn and Jason Eisner",
title = "Contextualization of Morphological Inflection",
booktitle = "Proceedings of the 2019 Conference of the North
American Chapter of the Association for Computational
Linguistics: Human Language Technologies (NAACL-HLT)",
pages = "2018--2024",
year = "2019",
month = jun,
address = "Minneapolis",
URL = "http://cs.jhu.edu/~jason/papers/#vylomova-et-al-2019",
}

H. Inaguma, S. Kiyono, N. E. Y. Soplin, J. Suzuki, K. Duh, and S. Watanabe, “ESPnet How2 Speech Translation System for IWSLT 2019: Pre-training, Knowledge Distillation, and Going Deeper,” in Proceedings of the 16th International Conference on Spoken Language Translation, Hong Kong, 2019.
[BibTeX] [Abstract] [Link]

This paper describes the ESPnet submissions to the How2 Speech Translation task at IWSLT2019. In this year, we mainly build our systems based on Transformer architectures in all tasks and focus on the end-to-end speech translation (E2E-ST). We first compare RNN-based models and Transformer, and then confirm Transformer models significantly and consistently outperform RNN models in all tasks and corpora. Next, we investigate pre-training of E2E-ST models with the ASR and MT tasks. On top of the pre-training, we further explore knowledge distillation from the NMT model and the deeper speech encoder, and confirm drastic improvements over the baseline model. All of our codes are publicly available in ESPnet.

@inproceedings{inaguma-etal-2019-espnet,
title = "{ESP}net How2 Speech Translation System for {IWSLT} 2019: Pre-training, Knowledge Distillation, and Going Deeper",
author = "Inaguma, Hirofumi and
Kiyono, Shun and
Soplin, Nelson Enrique Yalta and
Suzuki, Jun and
Duh, Kevin and
Watanabe, Shinji",
editor = {Niehues, Jan and
Cattoni, Rolando and
St{\"u}ker, Sebastian and
Negri, Matteo and
Turchi, Marco and
Ha, Thanh-Le and
Salesky, Elizabeth and
Sanabria, Ramon and
Barrault, Loic and
Specia, Lucia and
Federico, Marcello},
booktitle = "Proceedings of the 16th International Conference on Spoken Language Translation",
month = nov # " 2-3",
year = "2019",
address = "Hong Kong",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2019.iwslt-1.4",
abstract = "This paper describes the ESPnet submissions to the How2 Speech Translation task at IWSLT2019. In this year, we mainly build our systems based on Transformer architectures in all tasks and focus on the end-to-end speech translation (E2E-ST). We first compare RNN-based models and Transformer, and then confirm Transformer models significantly and consistently outperform RNN models in all tasks and corpora. Next, we investigate pre-training of E2E-ST models with the ASR and MT tasks. On top of the pre-training, we further explore knowledge distillation from the NMT model and the deeper speech encoder, and confirm drastic improvements over the baseline model. All of our codes are publicly available in ESPnet.",
}

J. Villalba, Nanxin Chen, David Snyder, D. Garcia-Romero, A. McCree, Gregory Sell, Jonas Borgstrom, Fred Richardson, Suwon Shon, François Grondin, Réda Dehak, Leibny Paola García-Perera, P. Torres-Carrasquillo, and N. Dehak, “The JHU-MIT System Description for NIST SRE18.” 2019.
[BibTeX] [Link]

@inproceedings{111380711,
title = {The JHU-MIT System Description for NIST SRE18},
author = {{J. Villalba} and {Nanxin Chen} and {David Snyder} and {D. Garcia-Romero} and {A. McCree} and {Gregory Sell} and {Jonas Borgstrom} and {Fred Richardson} and {Suwon Shon} and {François Grondin} and {Réda Dehak} and {Leibny Paola García-Perera} and {P. Torres-Carrasquillo} and {N. Dehak}},
year = 2019,
booktitle = {},
url = {https://www.semanticscholar.org/paper/00a4e57e9189162dc9875a1cdca527711f373b53},
}

B. Althouse, D. Weinberger, S. Scarpino, V. Pitzer, J. Ayers, E. Wenger, I. C. Fung, Mark Dredze, and Hao Hu, “Google searches accurately forecast RSV hospitalizations,” in bioRxiv, 2019.
[BibTeX] [Link]

@inproceedings{149763861,
title = {Google searches accurately forecast RSV hospitalizations},
author = {{B. Althouse} and {D. Weinberger} and {S. Scarpino} and {V. Pitzer} and {J. Ayers} and {E. Wenger} and {I. C. Fung} and {Mark Dredze} and {Hao Hu}},
year = 2019,
month = {4},
booktitle = {bioRxiv},
url = {https://www.semanticscholar.org/paper/2e5fe42de4e8d5482dacd794bbfb7c9e682bc079},
}

Tomas Figliolia and A. Andreou, “The Conical-Fishbone Clock Tree: A Clock-Distribution Network for a Heterogeneous Chip Multiprocessor AI Chiplet,” in Euromicro Symposium on Digital Systems Design, 2019.
[BibTeX] [Link]

@inproceedings{204822820,
title = {The Conical-Fishbone Clock Tree: A Clock-Distribution Network for a Heterogeneous Chip Multiprocessor AI Chiplet},
author = {{Tomas Figliolia} and {A. Andreou}},
year = 2019,
month = {8},
booktitle = {Euromicro Symposium on Digital Systems Design},
url = {https://www.semanticscholar.org/paper/4d5ce73c5dd4f1c2088e06f785094f70a7185438},
}

Kaitlin L. Fair, Daniel R. Mendat, A. Andreou, C. Rozell, J. Romberg, and David V. Anderson, “Sparse Coding Using the Locally Competitive Algorithm on the TrueNorth Neurosynaptic System,” in Frontiers in Neuroscience, 2019.
[BibTeX] [Link]

@inproceedings{198119979,
title = {Sparse Coding Using the Locally Competitive Algorithm on the TrueNorth Neurosynaptic System},
author = {{Kaitlin L. Fair} and {Daniel R. Mendat} and {A. Andreou} and {C. Rozell} and {J. Romberg} and {David V. Anderson}},
year = 2019,
month = {7},
booktitle = {Frontiers in Neuroscience},
url = {https://www.semanticscholar.org/paper/c97dd6ca7802bee7c6f25de29442d67c4971952d},
}

Kate D. Fischl, Adam B. Cellon, T. Stewart, T. Horiuchi, and A. Andreou, “Socio-Emotional Robot with Distributed Multi-Platform Neuromorphic Processing : (Invited Presentation),” in Annual Conference on Information Sciences and Systems, 2019.
[BibTeX] [Link]

@inproceedings{121383020,
title = {Socio-Emotional Robot with Distributed Multi-Platform Neuromorphic Processing : (Invited Presentation)},
author = {{Kate D. Fischl} and {Adam B. Cellon} and {T. Stewart} and {T. Horiuchi} and {A. Andreou}},
year = 2019,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/78b270c76998428dc56c0028997573eff899f032},
}

Cheng Peng, Wei-An Lin, Haofu Liao, R. Chellappa, and S. K. Zhou, “Deep Slice Interpolation via Marginal Super-Resolution, Fusion and Refinement,” in arXiv.org, 2019.
[BibTeX] [Link]

@inproceedings{199668810,
title = {Deep Slice Interpolation via Marginal Super-Resolution, Fusion and Refinement},
author = {{Cheng Peng} and {Wei-An Lin} and {Haofu Liao} and {R. Chellappa} and {S. K. Zhou}},
year = 2019,
month = {8},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/7145dcec0b06b9d2b0a2af564ded34eca138781c},
}

Nanxin Chen, J. Villalba, and N. Dehak, “Tied Mixture of Factor Analyzers Layer to Combine Frame Level Representations in Neural Speaker Embeddings,” in Interspeech, 2019.
[BibTeX] [Link]

@inproceedings{202706483,
title = {Tied Mixture of Factor Analyzers Layer to Combine Frame Level Representations in Neural Speaker Embeddings},
author = {{Nanxin Chen} and {J. Villalba} and {N. Dehak}},
year = 2019,
month = {9},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/f8799df9306ddf660f4ab1874bff154303042f00},
}

Pirazh Khorramshahi, Amit Kumar, Neehar Peri, Sai Saketh Rambhatla, Jun-Cheng Chen, and R. Chellappa, “A Dual-Path Model With Adaptive Attention for Vehicle Re-Identification,” in IEEE International Conference on Computer Vision, 2019.
[BibTeX] [Link]

@inproceedings{148572074,
title = {A Dual-Path Model With Adaptive Attention for Vehicle Re-Identification},
author = {{Pirazh Khorramshahi} and {Amit Kumar} and {Neehar Peri} and {Sai Saketh Rambhatla} and {Jun-Cheng Chen} and {R. Chellappa}},
year = 2019,
month = {5},
booktitle = {IEEE International Conference on Computer Vision},
url = {https://www.semanticscholar.org/paper/9f36e2c1307f32f5cda5965d609ba38e77c66772},
}

R. Arora and Jalaj Upadhyay, “On Differentially Private Graph Sparsification and Applications,” in Neural Information Processing Systems, 2019.
[BibTeX] [Link]

@inproceedings{202780841,
title = {On Differentially Private Graph Sparsification and Applications},
author = {{R. Arora} and {Jalaj Upadhyay}},
year = 2019,
booktitle = {Neural Information Processing Systems},
url = {https://www.semanticscholar.org/paper/70ea3519c15f768fb32a4a2aca0eec90d2b36bf7},
}

Tao Chen, Mark Dredze, J. Weiner, and Hadi Kharrazi, “Identifying vulnerable older adult populations by contextualizing geriatric syndrome information in clinical notes of electronic health records,” in J. Am. Medical Informatics Assoc., 2019.
[BibTeX] [Link]

@inproceedings{195772779,
title = {Identifying vulnerable older adult populations by contextualizing geriatric syndrome information in clinical notes of electronic health records},
author = {{Tao Chen} and {Mark Dredze} and {J. Weiner} and {Hadi Kharrazi}},
year = 2019,
month = {7},
booktitle = {J. Am. Medical Informatics Assoc.},
url = {https://www.semanticscholar.org/paper/4d0ae2ca26cc7e94eeff5c96a0d750213dce8dc5},
}

L. Moro-Velázquez, Jaejin Cho, Shinji Watanabe, M. Hasegawa-Johnson, O. Scharenborg, Heejin Kim, and N. Dehak, “Study of the Performance of Automatic Speech Recognition Systems in Speakers with Parkinson’s Disease,” in Interspeech, 2019.
[BibTeX] [Link]

@inproceedings{202741575,
title = {Study of the Performance of Automatic Speech Recognition Systems in Speakers with Parkinson's Disease},
author = {{L. Moro-Velázquez} and {Jaejin Cho} and {Shinji Watanabe} and {M. Hasegawa-Johnson} and {O. Scharenborg} and {Heejin Kim} and {N. Dehak}},
year = 2019,
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/4ab7b65e1a3b76eb3db064523c862f1325e04971},
}

Ilya Kavalerov, Weilin Li, W. Czaja, and R. Chellappa, “Three-Dimensional Fourier Scattering Transform and Classification of Hyperspectral Images,” in arXiv.org, 2019.
[BibTeX] [Link]

@inproceedings{189928551,
title = {Three-Dimensional Fourier Scattering Transform and Classification of Hyperspectral Images},
author = {{Ilya Kavalerov} and {Weilin Li} and {W. Czaja} and {R. Chellappa}},
year = 2019,
month = {6},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/abedc885c8b0588e2583dd7dc4863f07cfccd6e5},
}

Y. Balaji, R. Chellappa, and S. Feizi, “Normalized Wasserstein for Mixture Distributions With Applications in Adversarial Learning and Domain Adaptation,” in IEEE International Conference on Computer Vision, 2019.
[BibTeX] [Link]

@inproceedings{204961274,
title = {Normalized Wasserstein for Mixture Distributions With Applications in Adversarial Learning and Domain Adaptation},
author = {{Y. Balaji} and {R. Chellappa} and {S. Feizi}},
year = 2019,
month = {2},
booktitle = {IEEE International Conference on Computer Vision},
url = {https://www.semanticscholar.org/paper/e51d170dd4119ae1464c01fbb14e04e0ce8b3025},
}

Gaspar Tognetti, Jonah P. Sengupta, P. Pouliquen, and A. Andreou, “Characterization of a pseudo-DRAM Crossbar Computational Memory Array in 55nm CMOS : (Invited Paper),” in Annual Conference on Information Sciences and Systems, 2019.
[BibTeX] [Link]

@inproceedings{121333255,
title = {Characterization of a pseudo-DRAM Crossbar Computational Memory Array in 55nm CMOS : (Invited Paper)},
author = {{Gaspar Tognetti} and {Jonah P. Sengupta} and {P. Pouliquen} and {A. Andreou}},
year = 2019,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/5b8b185653130318cc2b8e2e60334cd1c35a6ea0},
}

Chen Change Loy, Xiaoming Liu, Tae-Kyun Kim, F. D. L. Torre, and R. Chellappa, “Editorial: Special Issue on Deep Learning for Face Analysis,” in International Journal of Computer Vision, 2019.
[BibTeX] [Link]

@inproceedings{146807919,
title = {Editorial: Special Issue on Deep Learning for Face Analysis},
author = {{Chen Change Loy} and {Xiaoming Liu} and {Tae-Kyun Kim} and {F. D. L. Torre} and {R. Chellappa}},
year = 2019,
month = {5},
booktitle = {International Journal of Computer Vision},
url = {https://www.semanticscholar.org/paper/381b434348fb74271913a786971b8fa0ffe982d5},
}

L. Moro-Velázquez, Jorge Andrés Gómez García, Juan Ignacio Godino-Llorente, J. Villalba, J. Rusz, S. Shattuck-Hufnagel, and N. Dehak, “A forced gaussians based methodology for the differential evaluation of Parkinson’s Disease by means of speech processing,” in Biomedical Signal Processing and Control, 2019.
[BibTeX] [Link]

@inproceedings{56486339,
title = {A forced gaussians based methodology for the differential evaluation of Parkinson's Disease by means of speech processing},
author = {{L. Moro-Velázquez} and {Jorge Andrés Gómez García} and {Juan Ignacio Godino-Llorente} and {J. Villalba} and {J. Rusz} and {S. Shattuck-Hufnagel} and {N. Dehak}},
year = 2019,
month = {2},
booktitle = {Biomedical Signal Processing and Control},
url = {https://www.semanticscholar.org/paper/56b464d01ac9f516e7078426327e31833010205c},
}

Y. Balaji, Martin Renqiang Min, Bing Bai, R. Chellappa, and H. Graf, “Conditional GAN with Discriminative Filter Generation for Text-to-Video Synthesis,” in International Joint Conference on Artificial Intelligence, 2019.
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@inproceedings{199465721,
title = {Conditional GAN with Discriminative Filter Generation for Text-to-Video Synthesis},
author = {{Y. Balaji} and {Martin Renqiang Min} and {Bing Bai} and {R. Chellappa} and {H. Graf}},
year = 2019,
month = {8},
booktitle = {International Joint Conference on Artificial Intelligence},
url = {https://www.semanticscholar.org/paper/f4c3d103d8ddb863d1e74e51d9ee2b3ef8529e30},
}

E. Leas, Mark Dredze, and J. Ayers, “Ignoring Data Delays Our Reaction to Emerging Public Health Tragedies Like 13 Reasons Why.,” in JAMA psychiatry, 2019.
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@inproceedings{202762315,
title = {Ignoring Data Delays Our Reaction to Emerging Public Health Tragedies Like 13 Reasons Why.},
author = {{E. Leas} and {Mark Dredze} and {J. Ayers}},
year = 2019,
booktitle = {JAMA psychiatry},
url = {https://www.semanticscholar.org/paper/ff75b93ee14abdeeac342b8e7153a8b618482833},
}

J. Ayers, A. Nobles, and Mark Dredze, “Media Trends for the Substance Abuse and Mental Health Services Administration 800-662-HELP Addiction Treatment Referral Services After a Celebrity Overdose,” in JAMA Internal Medicine, 2019.
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@inproceedings{58636432,
title = {Media Trends for the Substance Abuse and Mental Health Services Administration 800-662-HELP Addiction Treatment Referral Services After a Celebrity Overdose},
author = {{J. Ayers} and {A. Nobles} and {Mark Dredze}},
year = 2019,
month = {3},
booktitle = {JAMA Internal Medicine},
url = {https://www.semanticscholar.org/paper/ca40d3f8ac4ae4c831c08c6442e2dcff52067ad1},
}

David Snyder, J. Villalba, Nanxin Chen, Daniel Povey, Gregory Sell, N. Dehak, and S. Khudanpur, “The JHU Speaker Recognition System for the VOiCES 2019 Challenge,” in Interspeech, 2019.
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@inproceedings{202726162,
title = {The JHU Speaker Recognition System for the VOiCES 2019 Challenge},
author = {{David Snyder} and {J. Villalba} and {Nanxin Chen} and {Daniel Povey} and {Gregory Sell} and {N. Dehak} and {S. Khudanpur}},
year = 2019,
month = {9},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/aa3ba08a4451871da8a2e92ab11b3ed26c292bcf},
}

M. Naphade, Zheng Tang, Ming-Ching Chang, D. Anastasiu, Anuj Sharma, R. Chellappa, Shuo Wang, Pranamesh Chakraborty, Tingting Huang, Jenq-Neng Hwang, and Siwei Lyu, “The 2019 AI City Challenge,” in CVPR Workshops, 2019.
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@inproceedings{198350781,
title = {The 2019 AI City Challenge},
author = {{M. Naphade} and {Zheng Tang} and {Ming-Ching Chang} and {D. Anastasiu} and {Anuj Sharma} and {R. Chellappa} and {Shuo Wang} and {Pranamesh Chakraborty} and {Tingting Huang} and {Jenq-Neng Hwang} and {Siwei Lyu}},
year = 2019,
booktitle = {CVPR Workshops},
url = {https://www.semanticscholar.org/paper/fae3ff37995414fb9c5f1cac19301b7dff2f2bc8},
}

Cheng-I Lai, Nanxin Chen, J. Villalba, and N. Dehak, “ASSERT: Anti-Spoofing with Squeeze-Excitation and Residual neTworks,” in Interspeech, 2019.
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@inproceedings{91184432,
title = {ASSERT: Anti-Spoofing with Squeeze-Excitation and Residual neTworks},
author = {{Cheng-I Lai} and {Nanxin Chen} and {J. Villalba} and {N. Dehak}},
year = 2019,
month = {4},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/48ae745189239c05b41cceccfbecca138e4c2980},
}

Yuchen Zhou, Mark Dredze, David A. Broniatowski, and William D. Adler, “Elites and foreign actors among the alt-right: The Gab social media platform,” in First Monday, 2019.
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@inproceedings{202670330,
title = {Elites and foreign actors among the alt-right: The Gab social media platform},
author = {{Yuchen Zhou} and {Mark Dredze} and {David A. Broniatowski} and {William D. Adler}},
year = 2019,
month = {8},
booktitle = {First Monday},
url = {https://www.semanticscholar.org/paper/c28de758650461bbb039c9c71e9f2c7eb288d9b4},
}

Pirazh Khorramshahi, Neehar Peri, Amit Kumar, Anshul B. Shah, and R. Chellappa, “Attention Driven Vehicle Re-identification and Unsupervised Anomaly Detection for Traffic Understanding,” in CVPR Workshops, 2019.
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@inproceedings{198182536,
title = {Attention Driven Vehicle Re-identification and Unsupervised Anomaly Detection for Traffic Understanding},
author = {{Pirazh Khorramshahi} and {Neehar Peri} and {Amit Kumar} and {Anshul B. Shah} and {R. Chellappa}},
year = 2019,
booktitle = {CVPR Workshops},
url = {https://www.semanticscholar.org/paper/7c9f730a1b786b1d744bb1d6fdb20ee277428259},
}

Jingxiao Zheng, Ruichi Yu, Jun-Cheng Chen, Boyu Lu, C. Castillo, and R. Chellappa, “Uncertainty Modeling of Contextual-Connections Between Tracklets for Unconstrained Video-Based Face Recognition,” in IEEE International Conference on Computer Vision, 2019.
[BibTeX] [Link]

@inproceedings{147704141,
title = {Uncertainty Modeling of Contextual-Connections Between Tracklets for Unconstrained Video-Based Face Recognition},
author = {{Jingxiao Zheng} and {Ruichi Yu} and {Jun-Cheng Chen} and {Boyu Lu} and {C. Castillo} and {R. Chellappa}},
year = 2019,
month = {5},
booktitle = {IEEE International Conference on Computer Vision},
url = {https://www.semanticscholar.org/paper/1fe3019eecb975092b93062570a85a47588a2f8c},
}

Li Liu, Matti Pietik, Jie Chen, Guoying Zhao, Xiaogang Wang, and R. Chellappa, “’ Introduction to the Special 2 Section on Compact and Efficient Feature 3 Representation and Learning in Computer Vision.” 2019.
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title = {’ Introduction to the Special 2 Section on Compact and Efficient Feature 3 Representation and Learning in Computer Vision},
author = {{Li Liu} and {Matti Pietik} and {Jie Chen} and {Guoying Zhao} and {Xiaogang Wang} and {R. Chellappa}},
year = 2019,
booktitle = {},
url = {https://www.semanticscholar.org/paper/8e37eaa4c57208b70b8cb5b86311d7165da2dc3b},
}

Takafumi Moriya, Tomohiro Tanaka, T. Shinozaki, Shinji Watanabe, and Kevin Duh, “Evolution-Strategy-Based Automation of System Development for High-Performance Speech Recognition,” in IEEE/ACM Transactions on Audio Speech and Language Processing, 2019.
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author = {{Takafumi Moriya} and {Tomohiro Tanaka} and {T. Shinozaki} and {Shinji Watanabe} and {Kevin Duh}},
year = 2019,
month = {1},
booktitle = {IEEE/ACM Transactions on Audio Speech and Language Processing},
url = {https://www.semanticscholar.org/paper/5677d2b565c8265fef1693a9be861739cb01bf2f},
}

Jonah P. Sengupta, Gaspar Tognetti, P. Pouliquen, and A. Andreou, “Multilevel Storage Cell Characterization and Behavior Modeling of a Crossbar Computational Array in ESF3 Flash Technology : (Invited Paper),” in Annual Conference on Information Sciences and Systems, 2019.
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title = {Multilevel Storage Cell Characterization and Behavior Modeling of a Crossbar Computational Array in ESF3 Flash Technology : (Invited Paper)},
author = {{Jonah P. Sengupta} and {Gaspar Tognetti} and {P. Pouliquen} and {A. Andreou}},
year = 2019,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/19ad24c1762d140d80c2c5be7ef38f10eabf3966},
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Kayode A. Sanni and A. Andreou, “A Historical Perspective on Hardware AI Inference, Charge-Based Computational Circuits and an 8 bit Charge-Based Multiply-Add Core in 16 nm FinFET CMOS,” in IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2019.
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title = {A Historical Perspective on Hardware AI Inference, Charge-Based Computational Circuits and an 8 bit Charge-Based Multiply-Add Core in 16 nm FinFET CMOS},
author = {{Kayode A. Sanni} and {A. Andreou}},
year = 2019,
month = {8},
booktitle = {IEEE Journal on Emerging and Selected Topics in Circuits and Systems},
url = {https://www.semanticscholar.org/paper/9667928638bde6b32ca71367215bfd75ae700614},
}

Boyu Lu, Jun-Cheng Chen, and R. Chellappa, “Supplementary Materials-Unsupervised Domain-Specific Deblurring via Disentangled Representations.” 2019.
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title = {Supplementary Materials-Unsupervised Domain-Specific Deblurring via Disentangled Representations},
author = {{Boyu Lu} and {Jun-Cheng Chen} and {R. Chellappa}},
year = 2019,
booktitle = {},
url = {https://www.semanticscholar.org/paper/81c164685fc68af5f166a03d4add19eadf58d367},
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Suwon Shon, N. Dehak, D. Reynolds, and James R. Glass, “MCE 2018: The 1st Multi-target Speaker Detection and Identification Challenge Evaluation,” in Interspeech, 2019.
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title = {MCE 2018: The 1st Multi-target Speaker Detection and Identification Challenge Evaluation},
author = {{Suwon Shon} and {N. Dehak} and {D. Reynolds} and {James R. Glass}},
year = 2019,
month = {4},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/b3918fab36f106e83e016a3e33d260ad656191c4},
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R. Arora, T. V. Marinov, and M. Mohri, “Bandits with Feedback Graphs and Switching Costs,” in Neural Information Processing Systems, 2019.
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title = {Bandits with Feedback Graphs and Switching Costs},
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year = 2019,
month = {7},
booktitle = {Neural Information Processing Systems},
url = {https://www.semanticscholar.org/paper/5146f2b387efea0bd36ef2c38e01293eb29fa811},
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Nikita Ivkin, D. Rothchild, Enayat Ullah, V. Braverman, I. Stoica, and R. Arora, “Communication-efficient distributed SGD with Sketching,” in Neural Information Processing Systems, 2019.
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author = {{Nikita Ivkin} and {D. Rothchild} and {Enayat Ullah} and {V. Braverman} and {I. Stoica} and {R. Arora}},
year = 2019,
month = {3},
booktitle = {Neural Information Processing Systems},
url = {https://www.semanticscholar.org/paper/73b72bf922fd1f5b97fd5b7aa32ce748cad168ac},
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M. Rahman, Sorami Hisamoto, and Kevin Duh, “Query Expansion for Cross-Language Question Re-Ranking,” in arXiv.org, 2019.
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author = {{M. Rahman} and {Sorami Hisamoto} and {Kevin Duh}},
year = 2019,
month = {4},
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url = {https://www.semanticscholar.org/paper/d710f951db2b4b16b0d604917b7fcffa23c53c6d},
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Rajeev Ranjan, Vishal M. Patel, and R. Chellappa, “HyperFace: A Deep Multi-Task Learning Framework for Face Detection, Landmark Localization, Pose Estimation, and Gender Recognition,” in IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019.
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title = {HyperFace: A Deep Multi-Task Learning Framework for Face Detection, Landmark Localization, Pose Estimation, and Gender Recognition},
author = {{Rajeev Ranjan} and {Vishal M. Patel} and {R. Chellappa}},
year = 2019,
booktitle = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
url = {https://www.semanticscholar.org/paper/04eed24e26d9e6aaf2ca434cad20facd5feb83d0},
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G. D. Pais, Srikumar Ramalingam, V. Govindu, J. Nascimento, R. Chellappa, and Pedro Miraldo, “3DRegNet: A Deep Neural Network for 3D Point Registration,” in Computer Vision and Pattern Recognition, 2019.
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title = {3DRegNet: A Deep Neural Network for 3D Point Registration},
author = {{G. D. Pais} and {Srikumar Ramalingam} and {V. Govindu} and {J. Nascimento} and {R. Chellappa} and {Pedro Miraldo}},
year = 2019,
month = {4},
booktitle = {Computer Vision and Pattern Recognition},
url = {https://www.semanticscholar.org/paper/b5006eb94cee1a63bb78b3431bbdbe454b8ce0ef},
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Z. Tan, A. Sarkar, and N. Dehak, “rVAD: An Unsupervised Segment-Based Robust Voice Activity Detection Method,” in Computer Speech and Language, 2019.
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title = {rVAD: An Unsupervised Segment-Based Robust Voice Activity Detection Method},
author = {{Z. Tan} and {A. Sarkar} and {N. Dehak}},
year = 2019,
month = {6},
booktitle = {Computer Speech and Language},
url = {https://www.semanticscholar.org/paper/72eb5f52049ac2277a6d2502e8d88a34a5fcb4b8},
}

Pengcheng Xu, Prudhvi K. Gurram, Gene T. Whipps, and R. Chellappa, “Wasserstein Distance Based Domain Adaptation for Object Detection,” in arXiv.org, 2019.
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title = {Wasserstein Distance Based Domain Adaptation for Object Detection},
author = {{Pengcheng Xu} and {Prudhvi K. Gurram} and {Gene T. Whipps} and {R. Chellappa}},
year = 2019,
month = {9},
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url = {https://www.semanticscholar.org/paper/dce44773a8a4d150380af508b3939960adcc4f02},
}

Saurabhchand Bhati, Shekhar Nayak, K. Murty, and N. Dehak, “Unsupervised Acoustic Segmentation and Clustering Using Siamese Network Embeddings,” in Interspeech, 2019.
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title = {Unsupervised Acoustic Segmentation and Clustering Using Siamese Network Embeddings},
author = {{Saurabhchand Bhati} and {Shekhar Nayak} and {K. Murty} and {N. Dehak}},
year = 2019,
month = {9},
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url = {https://www.semanticscholar.org/paper/110a9c92bd185f8cea29105cd8d7176534e3383b},
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J. Villalba, D. Garcia-Romero, Nanxin Chen, Gregory Sell, Jonas Borgstrom, A. McCree, David Snyder, Saurabh Kataria, Leibny Paola García-Perera, Fred Richardson, P. Torres-Carrasquillo, and N. Dehak, “The JHU-MIT System Description for NIST SRE19 AV.” 2019.
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year = 2019,
booktitle = {},
url = {https://www.semanticscholar.org/paper/ea4fd6b3527e913a038c8ad66e3a2ee1e0adf0c7},
}

J. Villalba, Nanxin Chen, David Snyder, D. Garcia-Romero, A. McCree, Gregory Sell, Jonas Borgstrom, Fred Richardson, Suwon Shon, François Grondin, Réda Dehak, Leibny Paola García-Perera, Daniel Povey, P. Torres-Carrasquillo, S. Khudanpur, and N. Dehak, “State-of-the-Art Speaker Recognition for Telephone and Video Speech: The JHU-MIT Submission for NIST SRE18,” in Interspeech, 2019.
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title = {State-of-the-Art Speaker Recognition for Telephone and Video Speech: The JHU-MIT Submission for NIST SRE18},
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year = 2019,
month = {9},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/2d198d5209b9f144378ff1f86ce8bfc36249669e},
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P. S. Nidadavolu, J. Villalba, and N. Dehak, “Cycle-GANs for Domain Adaptation of Acoustic Features for Speaker Recognition,” in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2019.
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month = {5},
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url = {https://www.semanticscholar.org/paper/20719e4f29ed1ffc06b4281f2446798e1571ebd7},
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B. Althouse, D. Weinberger, S. Scarpino, V. Pitzer, J. Ayers, E. Wenger, I. C. Fung, Mark Dredze, and Hao Hu, “GOOGLE SEARCHES ACCURATELY FORECAST RESPIRATORY SYNCYTIAL VIRUS HOSPITALIZATIONS,” in Chest, 2019.
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title = {GOOGLE SEARCHES ACCURATELY FORECAST RESPIRATORY SYNCYTIAL VIRUS HOSPITALIZATIONS},
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year = 2019,
month = {4},
booktitle = {Chest},
url = {https://www.semanticscholar.org/paper/53025df53d3c1fb3afe10b72784cd0b9d724a876},
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Ankan Bansal, Sai Saketh Rambhatla, Abhinav Shrivastava, and R. Chellappa, “Detecting Human-Object Interactions via Functional Generalization,” in AAAI Conference on Artificial Intelligence, 2019.
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title = {Detecting Human-Object Interactions via Functional Generalization},
author = {{Ankan Bansal} and {Sai Saketh Rambhatla} and {Abhinav Shrivastava} and {R. Chellappa}},
year = 2019,
month = {4},
booktitle = {AAAI Conference on Artificial Intelligence},
url = {https://www.semanticscholar.org/paper/b3ca33cebdb225d81450af8f47b63ce7f78d0bb1},
}

Cheng Peng, Wei-An Lin, R. Chellappa, and S. K. Zhou, “Towards multi-sequence MR image recovery from undersampled k-space data,” in International Conference on Medical Imaging with Deep Learning, 2019.
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title = {Towards multi-sequence MR image recovery from undersampled k-space data},
author = {{Cheng Peng} and {Wei-An Lin} and {R. Chellappa} and {S. K. Zhou}},
year = 2019,
month = {8},
booktitle = {International Conference on Medical Imaging with Deep Learning},
url = {https://www.semanticscholar.org/paper/fbc4d42a37c7dfb4622123002dc4c21471016d36},
}

Mohammed Senoussaoui, P. Cardinal, N. Dehak, and Alessandro Lameiras Koerich, “Speaker Sincerity Detection based on Covariance Feature Vectors and Ensemble Methods,” in arXiv.org, 2019.
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title = {Speaker Sincerity Detection based on Covariance Feature Vectors and Ensemble Methods},
author = {{Mohammed Senoussaoui} and {P. Cardinal} and {N. Dehak} and {Alessandro Lameiras Koerich}},
year = 2019,
month = {4},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/1278d874aef57ac09eaeb51e5a50e2568bb7d0bd},
}

Arthita Ghosh, Max Ehrlich, L. Davis, and R. Chellappa, “Unsupervised Super-Resolution of Satellite Imagery for High Fidelity Material Label Transfer,” in IEEE International Geoscience and Remote Sensing Symposium, 2019.
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title = {Unsupervised Super-Resolution of Satellite Imagery for High Fidelity Material Label Transfer},
author = {{Arthita Ghosh} and {Max Ehrlich} and {L. Davis} and {R. Chellappa}},
year = 2019,
month = {7},
booktitle = {IEEE International Geoscience and Remote Sensing Symposium},
url = {https://www.semanticscholar.org/paper/22188016c5deab12322ead9d0baa863a2b3de945},
}

Boyu Lu, Jun-Cheng Chen, and R. Chellappa, “Unsupervised Domain-Specific Deblurring via Disentangled Representations,” in Computer Vision and Pattern Recognition, 2019.
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title = {Unsupervised Domain-Specific Deblurring via Disentangled Representations},
author = {{Boyu Lu} and {Jun-Cheng Chen} and {R. Chellappa}},
year = 2019,
month = {3},
booktitle = {Computer Vision and Pattern Recognition},
url = {https://www.semanticscholar.org/paper/7834636155c6df9e674317ab2d151aace11ecc21},
}

M. Kaufman, D. Dey, C. Crainiceanu, and Mark Dredze, “#MeToo and Google Inquiries Into Sexual Violence: A Hashtag Campaign Can Sustain Information Seeking,” in Journal of Interpersonal Violence, 2019.
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title = {#MeToo and Google Inquiries Into Sexual Violence: A Hashtag Campaign Can Sustain Information Seeking},
author = {{M. Kaufman} and {D. Dey} and {C. Crainiceanu} and {Mark Dredze}},
year = 2019,
month = {8},
booktitle = {Journal of Interpersonal Violence},
url = {https://www.semanticscholar.org/paper/6b799cc68e736b4ae5dd31e6d34222b1d4452b64},
}

Huda Khayrallah, Rebecca Knowles, Kevin Duh, and Matt Post, “An Interactive Teaching Tool for Introducing Novices to Machine Translation,” in Technical Symposium on Computer Science Education, 2019.
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title = {An Interactive Teaching Tool for Introducing Novices to Machine Translation},
author = {{Huda Khayrallah} and {Rebecca Knowles} and {Kevin Duh} and {Matt Post}},
year = 2019,
month = {2},
booktitle = {Technical Symposium on Computer Science Education},
url = {https://www.semanticscholar.org/paper/d9cdd925890585552f16d69c28bb32a8ffbaef6c},
}

Poorya Mianjy and R. Arora, “On Dropout and Nuclear Norm Regularization,” in International Conference on Machine Learning, 2019.
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title = {On Dropout and Nuclear Norm Regularization},
author = {{Poorya Mianjy} and {R. Arora}},
year = 2019,
month = {5},
booktitle = {International Conference on Machine Learning},
url = {https://www.semanticscholar.org/paper/c98c286aae6407b03b0ee2d1adb131ad554ae225},
}

Andrew Zisserman, Greg Knowles, Berthold K. P. Horn, Anna R. Bruss, R. Chellappa, M. Brooks, and R. W. Sjoberg, “Photometric Invariants Related to Solid Shape 301.” 2019.
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title = {Photometric Invariants Related to Solid Shape 301},
author = {{Andrew Zisserman} and {Greg Knowles} and {Berthold K. P. Horn} and {Anna R. Bruss} and {R. Chellappa} and {M. Brooks} and {R. W. Sjoberg}},
year = 2019,
booktitle = {},
url = {https://www.semanticscholar.org/paper/14272e390ca37424133f7838eb53f36e12fb5a7b},
}

P. S. Nidadavolu, Vicente A. Iglesias, J. Villalba, and N. Dehak, “Investigation on Neural Bandwidth Extension of Telephone Speech for Improved Speaker Recognition,” in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2019.
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title = {Investigation on Neural Bandwidth Extension of Telephone Speech for Improved Speaker Recognition},
author = {{P. S. Nidadavolu} and {Vicente A. Iglesias} and {J. Villalba} and {N. Dehak}},
year = 2019,
month = {5},
booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
url = {https://www.semanticscholar.org/paper/00226bc35b3c8c107814b7760c22a983af097729},
}

Prithviraj Dhar, C. Castillo, and R. Chellappa, “On Measuring the Iconicity of a Face,” in IEEE Workshop/Winter Conference on Applications of Computer Vision, 2019.
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title = {On Measuring the Iconicity of a Face},
author = {{Prithviraj Dhar} and {C. Castillo} and {R. Chellappa}},
year = 2019,
month = {1},
booktitle = {IEEE Workshop/Winter Conference on Applications of Computer Vision},
url = {https://www.semanticscholar.org/paper/a5f80b45ba1339f68798d7d1591d690ee249a60e},
}

R. Arora and T. V. Marinov, “Efficient Convex Relaxations for Streaming PCA,” in Neural Information Processing Systems, 2019.
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title = {Efficient Convex Relaxations for Streaming PCA},
author = {{R. Arora} and {T. V. Marinov}},
year = 2019,
booktitle = {Neural Information Processing Systems},
url = {https://www.semanticscholar.org/paper/0b354c7d1112b8645fb9e4328cc4fc15b4a3f412},
}

A. Andreou and Daniel R. Mendat, “Graphical Model Transformation Analysis for Cognitive Computing and Machine Learning on the SpiNNaker Chip Multiprocessor,” in Euromicro Symposium on Digital Systems Design, 2019.
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title = {Graphical Model Transformation Analysis for Cognitive Computing and Machine Learning on the SpiNNaker Chip Multiprocessor},
author = {{A. Andreou} and {Daniel R. Mendat}},
year = 2019,
month = {8},
booktitle = {Euromicro Symposium on Digital Systems Design},
url = {https://www.semanticscholar.org/paper/109e16dcd24bbb1a8c676f7a4f15c4d8ab3fe0a7},
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Elliot Schumacher and Mark Dredze, “Discriminative Candidate Generation for Medical Concept Linking,” in Conference on Automated Knowledge Base Construction, 2019.
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title = {Discriminative Candidate Generation for Medical Concept Linking},
author = {{Elliot Schumacher} and {Mark Dredze}},
year = 2019,
month = {4},
booktitle = {Conference on Automated Knowledge Base Construction},
url = {https://www.semanticscholar.org/paper/46006a93c3d2a0398473906dcbbb1863ee7413ac},
}

Jingxiao Zheng, Ruichi Yu, Jun-Cheng Chen, Boyu Lu, C. Castillo, and R. Chellappa, “Supplementary Material of Modeling the Uncertainty of Contextual-Connections between Tracklets for Unconstrained Video-based Face Recognition.” 2019.
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title = {Supplementary Material of Modeling the Uncertainty of Contextual-Connections between Tracklets for Unconstrained Video-based Face Recognition},
author = {{Jingxiao Zheng} and {Ruichi Yu} and {Jun-Cheng Chen} and {Boyu Lu} and {C. Castillo} and {R. Chellappa}},
year = 2019,
booktitle = {},
url = {https://www.semanticscholar.org/paper/eaeea227a426a90e73bfe6527db6fab23632a492},
}

Amit Kumar and R. Chellappa, “Landmark Detection in Low Resolution Faces with Semi-Supervised Learning,” in arXiv.org, 2019.
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@inproceedings{199001178,
title = {Landmark Detection in Low Resolution Faces with Semi-Supervised Learning},
author = {{Amit Kumar} and {R. Chellappa}},
year = 2019,
month = {7},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/f0928c32a9b483dc0a0e6b34fa356ba525622edb},
}

Xiaolei Huang, Michael C. Smith, Amelia M. Jamison, David A. Broniatowski, Mark Dredze, S. Quinn, Justin Cai, and Michael J. Paul, “Can online self-reports assist in real-time identification of influenza vaccination uptake? A cross-sectional study of influenza vaccine-related tweets in the USA, 2013–2017,” in BMJ Open, 2019.
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title = {Can online self-reports assist in real-time identification of influenza vaccination uptake? A cross-sectional study of influenza vaccine-related tweets in the USA, 2013–2017},
author = {{Xiaolei Huang} and {Michael C. Smith} and {Amelia M. Jamison} and {David A. Broniatowski} and {Mark Dredze} and {S. Quinn} and {Justin Cai} and {Michael J. Paul}},
year = 2019,
month = {1},
booktitle = {BMJ Open},
url = {https://www.semanticscholar.org/paper/a6b686007046cfd0d5bc1ee2de92f228bbe178c6},
}

Jingxiao Zheng, Rajeev Ranjan, Ching-Hui Chen, Jun-Cheng Chen, C. Castillo, and R. Chellappa, “Face Detection Model LearningInput Videos Matching Subspaces Exemplars DCNN Features Subspaces And Exemplars Face Classifier Deep Feature Extraction Face Association Face Bounding Boxes Face Detector Face Sets and Feature Sets Multiple-Shot Association Single-Shot Association OR Target Subject Targe.” 2019.
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@inproceedings{199555327,
title = {Face Detection Model LearningInput Videos Matching Subspaces Exemplars DCNN Features Subspaces And Exemplars Face Classifier Deep Feature Extraction Face Association Face Bounding Boxes Face Detector Face Sets and Feature Sets Multiple-Shot Association Single-Shot Association OR Target Subject Targe},
author = {{Jingxiao Zheng} and {Rajeev Ranjan} and {Ching-Hui Chen} and {Jun-Cheng Chen} and {C. Castillo} and {R. Chellappa}},
year = 2019,
booktitle = {},
url = {https://www.semanticscholar.org/paper/a90f42b62576cdc0652af39bf8a4c8309289da55},
}

Wei-An Lin, Haofu Liao, Cheng Peng, Xiaohang Sun, Jingdan Zhang, Jiebo Luo, R. Chellappa, and S. Zhou, “DuDoNet: Dual Domain Network for CT Metal Artifact Reduction,” in Computer Vision and Pattern Recognition, 2019.
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@inproceedings{195767157,
title = {DuDoNet: Dual Domain Network for CT Metal Artifact Reduction},
author = {{Wei-An Lin} and {Haofu Liao} and {Cheng Peng} and {Xiaohang Sun} and {Jingdan Zhang} and {Jiebo Luo} and {R. Chellappa} and {S. Zhou}},
year = 2019,
month = {6},
booktitle = {Computer Vision and Pattern Recognition},
url = {https://www.semanticscholar.org/paper/3ad2414d272fce5eec4f3bc1b01e1dc9027c47bf},
}

Mousmita Sarma, Pegah Ghahremani, Daniel Povey, N. Goel, K. K. Sarma, and N. Dehak, “Improving Emotion Identification Using Phone Posteriors in Raw Speech Waveform Based DNN,” in Interspeech, 2019.
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@inproceedings{202724212,
title = {Improving Emotion Identification Using Phone Posteriors in Raw Speech Waveform Based DNN},
author = {{Mousmita Sarma} and {Pegah Ghahremani} and {Daniel Povey} and {N. Goel} and {K. K. Sarma} and {N. Dehak}},
year = 2019,
month = {9},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/d8d6ce03b270fbd5e31f9a8fff7af5b39ad5902e},
}

H. Inaguma, Kevin Duh, Tatsuya Kawahara, and Shinji Watanabe, “C L ] 1 O ct 2 01 9 MULTILINGUAL END-TO-END SPEECH TRANSLATION.” 2019.
[BibTeX] [Link]

@inproceedings{203657197,
title = {C L ] 1 O ct 2 01 9 MULTILINGUAL END-TO-END SPEECH TRANSLATION},
author = {{H. Inaguma} and {Kevin Duh} and {Tatsuya Kawahara} and {Shinji Watanabe}},
year = 2019,
booktitle = {},
url = {https://www.semanticscholar.org/paper/ffecb8b8b415149f5351b64a2dbb1a1fa64219f0},
}

A. Pasciaroni, Pedro Julian, and A. Andreou, “Parallelism Analysis for a Multi-core Speech Recognition Architecture,” in International Symposium on Computational Aesthetics in Graphics, Visualization, and Imaging, 2019.
[BibTeX] [Link]

@inproceedings{148574530,
title = {Parallelism Analysis for a Multi-core Speech Recognition Architecture},
author = {{A. Pasciaroni} and {Pedro Julian} and {A. Andreou}},
year = 2019,
month = {3},
booktitle = {International Symposium on Computational Aesthetics in Graphics, Visualization, and Imaging},
url = {https://www.semanticscholar.org/paper/00b82373ebb13eeefa248b44c76084134b2a21e6},
}

A. Nobles, Mark Dredze, and J. Ayers, ““Repeal and replace”: increased demand for intrauterine devices following the 2016 presidential election,” in Contraception, 2019.
[BibTeX] [Link]

@inproceedings{88227084,
title = {“Repeal and replace”: increased demand for intrauterine devices following the 2016 presidential election},
author = {{A. Nobles} and {Mark Dredze} and {J. Ayers}},
year = 2019,
month = {5},
booktitle = {Contraception},
url = {https://www.semanticscholar.org/paper/b0252c18479da00eaa6fc160d92757ad6b01a223},
}

S. J. Mielke and J. Eisner, “Spell Once, Summon Anywhere: A Two-Level Open-Vocabulary Language Model,” in Proceedings of the 33rd AAAI Conference on Artificial Intelligence, Honolulu, 2019, p. 6843–6850. doi:10.1609/aaai.v33i01.33016843
[BibTeX] [Link]

@InProceedings{mielke-eisner-2019,
doi = "10.1609/aaai.v33i01.33016843",
author = "Sabrina J. Mielke and Jason Eisner",
title = "Spell Once, Summon Anywhere: {A} Two-Level
Open-Vocabulary Language Model",
booktitle = "Proceedings of the 33rd AAAI Conference on Artificial
Intelligence",
pages = "6843--6850",
year = "2019",
month = jan,
address = "Honolulu",
URL = "http://cs.jhu.edu/~jason/papers/#mielke-eisner-2019",
}

Jingxiao Zheng, Rajeev Ranjan, Ching-Hui Chen, Jun-Cheng Chen, C. Castillo, and R. Chellappa, “An Automatic System for Unconstrained Video-Based Face Recognition,” in IEEE Transactions on Biometrics Behavior and Identity Science, 2018.
[BibTeX] [Link]

@inproceedings{54549797,
title = {An Automatic System for Unconstrained Video-Based Face Recognition},
author = {{Jingxiao Zheng} and {Rajeev Ranjan} and {Ching-Hui Chen} and {Jun-Cheng Chen} and {C. Castillo} and {R. Chellappa}},
year = 2018,
month = {12},
booktitle = {IEEE Transactions on Biometrics Behavior and Identity Science},
url = {https://www.semanticscholar.org/paper/da3f1fd1362426540d66c9f993469f50dacddc99},
}

N. Dehak, “Evaluation of Neurological Diseases by Means of Speech Processing and Multimodal Analysis,” in IEEE Signal Processing in Medicine and Biology Symposium, 2018.
[BibTeX] [Link]

@inproceedings{58669977,
title = {Evaluation of Neurological Diseases by Means of Speech Processing and Multimodal Analysis},
author = {{N. Dehak}},
year = 2018,
month = {12},
booktitle = {IEEE Signal Processing in Medicine and Biology Symposium},
url = {https://www.semanticscholar.org/paper/c59513c624e1f54bd78809efb8ccd5bea7dce50f},
}

Matthew Wiesner, Adithya Renduchintala, Shinji Watanabe, Chunxi Liu, N. Dehak, and S. Khudanpur, “Pretraining by Backtranslation for End-to-End ASR in Low-Resource Settings,” in Interspeech, 2018.
[BibTeX] [Link]

@inproceedings{199442340,
title = {Pretraining by Backtranslation for End-to-End ASR in Low-Resource Settings},
author = {{Matthew Wiesner} and {Adithya Renduchintala} and {Shinji Watanabe} and {Chunxi Liu} and {N. Dehak} and {S. Khudanpur}},
year = 2018,
month = {12},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/bd8922f8cc8284553dc9e6db529af309298451fe},
}

Mohammed E. Fathy, A. Alavi, and R. Chellappa, “Nonlinear Subspace Feature Enhancement for Image Set Classification,” in Asian Conference on Computer Vision, 2018.
[BibTeX] [Link]

@inproceedings{167210438,
title = {Nonlinear Subspace Feature Enhancement for Image Set Classification},
author = {{Mohammed E. Fathy} and {A. Alavi} and {R. Chellappa}},
year = 2018,
month = {12},
booktitle = {Asian Conference on Computer Vision},
url = {https://www.semanticscholar.org/paper/12a15dfa452c7bbf7ee8d149d5141f6ed7c8e485},
}

Y. Balaji, S. Sankaranarayanan, and R. Chellappa, “MetaReg: Towards Domain Generalization using Meta-Regularization,” in Neural Information Processing Systems, 2018.
[BibTeX] [Link]

@inproceedings{53979606,
title = {MetaReg: Towards Domain Generalization using Meta-Regularization},
author = {{Y. Balaji} and {S. Sankaranarayanan} and {R. Chellappa}},
year = 2018,
month = {12},
booktitle = {Neural Information Processing Systems},
url = {https://www.semanticscholar.org/paper/3dd8bf5cca76b1690a2642b73b509fb3a27e4f36},
}

Nils Holzenberger, Shruti Palaskar, P. Madhyastha, Florian Metze, and R. Arora, “Learning from Multiview Correlations in Open-domain Videos,” in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2018.
[BibTeX] [Link]

@inproceedings{53717388,
title = {Learning from Multiview Correlations in Open-domain Videos},
author = {{Nils Holzenberger} and {Shruti Palaskar} and {P. Madhyastha} and {Florian Metze} and {R. Arora}},
year = 2018,
month = {11},
booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
url = {https://www.semanticscholar.org/paper/a01ae256dfe7bd10734fec8a66549fb7ea876a05},
}

J. Ayers, Mark Dredze, E. Leas, Theodore L. Caputi, Jon-Patrick Allem, and Joanna E. Cohen, “Next generation media monitoring: Global coverage of electronic nicotine delivery systems (electronic cigarettes) on Bing, Google and Twitter, 2013-2018,” in PLoS ONE, 2018.
[BibTeX] [Link]

@inproceedings{53268904,
title = {Next generation media monitoring: Global coverage of electronic nicotine delivery systems (electronic cigarettes) on Bing, Google and Twitter, 2013-2018},
author = {{J. Ayers} and {Mark Dredze} and {E. Leas} and {Theodore L. Caputi} and {Jon-Patrick Allem} and {Joanna E. Cohen}},
year = 2018,
month = {11},
booktitle = {PLoS ONE},
url = {https://www.semanticscholar.org/paper/637ed794b41f2a50f8b2efce4ef02b3b12c8c057},
}

A. Benton and M. Dredze, “Using Author Embeddings to Improve Tweet Stance Classification,” in Proceedings of the 2018 EMNLP Workshop W-NUT: The 4th Workshop on Noisy User-generated Text, Brussels, Belgium, 2018, p. 184–194. doi:10.18653/v1/W18-6124
[BibTeX] [Abstract] [Link]

Many social media classification tasks analyze the content of a message, but do not consider the context of the message. For example, in tweet stance classification {–} where a tweet is categorized according to a viewpoint it espouses {–} the expressed viewpoint depends on latent beliefs held by the user. In this paper we investigate whether incorporating knowledge about the author can improve tweet stance classification. Furthermore, since author information and embeddings are often unavailable for labeled training examples, we propose a semi-supervised pretraining method to predict user embeddings. Although the neural stance classifiers we learn are often outperformed by a baseline SVM, author embedding pre-training yields improvements over a non-pre-trained neural network on four out of five domains in the SemEval 2016 6A tweet stance classification task. In a tweet gun control stance classification dataset, improvements from pre-training are only apparent when training data is limited.

@inproceedings{benton-dredze-2018-using,
title = "Using Author Embeddings to Improve Tweet Stance Classification",
author = "Benton, Adrian and
Dredze, Mark",
editor = "Xu, Wei and
Ritter, Alan and
Baldwin, Tim and
Rahimi, Afshin",
booktitle = "Proceedings of the 2018 {EMNLP} Workshop W-{NUT}: The 4th Workshop on Noisy User-generated Text",
month = nov,
year = "2018",
address = "Brussels, Belgium",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-6124",
doi = "10.18653/v1/W18-6124",
pages = "184--194",
abstract = "Many social media classification tasks analyze the content of a message, but do not consider the context of the message. For example, in tweet stance classification {--} where a tweet is categorized according to a viewpoint it espouses {--} the expressed viewpoint depends on latent beliefs held by the user. In this paper we investigate whether incorporating knowledge about the author can improve tweet stance classification. Furthermore, since author information and embeddings are often unavailable for labeled training examples, we propose a semi-supervised pretraining method to predict user embeddings. Although the neural stance classifiers we learn are often outperformed by a baseline SVM, author embedding pre-training yields improvements over a non-pre-trained neural network on four out of five domains in the SemEval 2016 6A tweet stance classification task. In a tweet gun control stance classification dataset, improvements from pre-training are only apparent when training data is limited.",
}

Hongyu Xu, Xutao Lv, Xiaoyu Wang, Zhou Ren, and R. Chellappa, “Deep Regionlets: Blended Representation and Deep Learning for Generic Object Detection,” in IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018.
[BibTeX] [Link]

@inproceedings{53865412,
title = {Deep Regionlets: Blended Representation and Deep Learning for Generic Object Detection},
author = {{Hongyu Xu} and {Xutao Lv} and {Xiaoyu Wang} and {Zhou Ren} and {R. Chellappa}},
year = 2018,
month = {11},
booktitle = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
url = {https://www.semanticscholar.org/paper/5232d6cba44a7bb67e8627ce4c2f4f93dce31e47},
}

R. Arora, M. Dinitz, T. V. Marinov, and M. Mohri, “Policy Regret in Repeated Games,” in Neural Information Processing Systems, 2018.
[BibTeX] [Link]

@inproceedings{53285373,
title = {Policy Regret in Repeated Games},
author = {{R. Arora} and {M. Dinitz} and {T. V. Marinov} and {M. Mohri}},
year = 2018,
month = {11},
booktitle = {Neural Information Processing Systems},
url = {https://www.semanticscholar.org/paper/c1482f2409af234da7d9771ddac4e88b45ec8e86},
}

Z. Wood-Doughty, N. Andrews, and M. Dredze, “Convolutions Are All You Need (For Classifying Character Sequences),” in Proceedings of the 2018 EMNLP Workshop W-NUT: The 4th Workshop on Noisy User-generated Text, Brussels, Belgium, 2018, p. 208–213. doi:10.18653/v1/W18-6127
[BibTeX] [Abstract] [Link]

While recurrent neural networks (RNNs) are widely used for text classification, they demonstrate poor performance and slow convergence when trained on long sequences. When text is modeled as characters instead of words, the longer sequences make RNNs a poor choice. Convolutional neural networks (CNNs), although somewhat less ubiquitous than RNNs, have an internal structure more appropriate for long-distance character dependencies. To better understand how CNNs and RNNs differ in handling long sequences, we use them for text classification tasks in several character-level social media datasets. The CNN models vastly outperform the RNN models in our experiments, suggesting that CNNs are superior to RNNs at learning to classify character-level data.

@inproceedings{wood-doughty-etal-2018-convolutions,
title = "Convolutions Are All You Need (For Classifying Character Sequences)",
author = "Wood-Doughty, Zach and
Andrews, Nicholas and
Dredze, Mark",
editor = "Xu, Wei and
Ritter, Alan and
Baldwin, Tim and
Rahimi, Afshin",
booktitle = "Proceedings of the 2018 {EMNLP} Workshop W-{NUT}: The 4th Workshop on Noisy User-generated Text",
month = nov,
year = "2018",
address = "Brussels, Belgium",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-6127",
doi = "10.18653/v1/W18-6127",
pages = "208--213",
abstract = "While recurrent neural networks (RNNs) are widely used for text classification, they demonstrate poor performance and slow convergence when trained on long sequences. When text is modeled as characters instead of words, the longer sequences make RNNs a poor choice. Convolutional neural networks (CNNs), although somewhat less ubiquitous than RNNs, have an internal structure more appropriate for long-distance character dependencies. To better understand how CNNs and RNNs differ in handling long sequences, we use them for text classification tasks in several character-level social media datasets. The CNN models vastly outperform the RNN models in our experiments, suggesting that CNNs are superior to RNNs at learning to classify character-level data.",
}

Amit Kumar, A. Alavi, and R. Chellappa, “KEPLER: Simultaneous estimation of keypoints and 3D pose of unconstrained faces in a unified framework by learning efficient H-CNN regressors,” in Image and Vision Computing, 2018.
[BibTeX] [Link]

@inproceedings{53115077,
title = {KEPLER: Simultaneous estimation of keypoints and 3D pose of unconstrained faces in a unified framework by learning efficient H-CNN regressors},
author = {{Amit Kumar} and {A. Alavi} and {R. Chellappa}},
year = 2018,
month = {11},
booktitle = {Image and Vision Computing},
url = {https://www.semanticscholar.org/paper/e8d98b76d82065abfcf20194918a737b7e5e4c4b},
}

Xuan Zhang, Manish Kumar, Huda Khayrallah, Kenton Murray, Jeremy Gwinnup, Marianna J. Martindale, Paul McNamee, Kevin Duh, and Marine Carpuat, “An Empirical Exploration of Curriculum Learning for Neural Machine Translation,” in arXiv.org, 2018.
[BibTeX] [Link]

@inproceedings{53295888,
title = {An Empirical Exploration of Curriculum Learning for Neural Machine Translation},
author = {{Xuan Zhang} and {Manish Kumar} and {Huda Khayrallah} and {Kenton Murray} and {Jeremy Gwinnup} and {Marianna J. Martindale} and {Paul McNamee} and {Kevin Duh} and {Marine Carpuat}},
year = 2018,
month = {11},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/b43ffb0d4f8d1c66632b78ad74d92ab1218a6976},
}

Zili Huang, Leibny Paola García-Perera, J. Villalba, Daniel Povey, and N. Dehak, “JHU Diarization System Description,” in IberSPEECH Conference, 2018.
[BibTeX] [Link]

@inproceedings{54177614,
title = {JHU Diarization System Description},
author = {{Zili Huang} and {Leibny Paola García-Perera} and {J. Villalba} and {Daniel Povey} and {N. Dehak}},
year = 2018,
month = {11},
booktitle = {IberSPEECH Conference},
url = {https://www.semanticscholar.org/paper/23a109da0c4ce0314f6f016da679a4e1fd6960ef},
}

Prithviraj Dhar, Rajat Vikram Singh, Kuan-Chuan Peng, Ziyan Wu, and R. Chellappa, “Learning Without Memorizing,” in Computer Vision and Pattern Recognition, 2018.
[BibTeX] [Link]

@inproceedings{53776855,
title = {Learning Without Memorizing},
author = {{Prithviraj Dhar} and {Rajat Vikram Singh} and {Kuan-Chuan Peng} and {Ziyan Wu} and {R. Chellappa}},
year = 2018,
month = {11},
booktitle = {Computer Vision and Pattern Recognition},
url = {https://www.semanticscholar.org/paper/162a4c6f964880ec90b40fefa6d4d99d3ad321ec},
}

Jaejin Cho, Shinji Watanabe, Takaaki Hori, M. Baskar, H. Inaguma, J. Villalba, and N. Dehak, “Language Model Integration Based on Memory Control for Sequence to Sequence Speech Recognition,” in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2018.
[BibTeX] [Link]

@inproceedings{53245942,
title = {Language Model Integration Based on Memory Control for Sequence to Sequence Speech Recognition},
author = {{Jaejin Cho} and {Shinji Watanabe} and {Takaaki Hori} and {M. Baskar} and {H. Inaguma} and {J. Villalba} and {N. Dehak}},
year = 2018,
month = {11},
booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
url = {https://www.semanticscholar.org/paper/8f963beca679cb1129df0a944c6de4b126e20fd5},
}

Joshua Gleason, Rajeev Ranjan, S. Schwarcz, C. Castillo, Jun-Cheng Chen, and R. Chellappa, “A Proposal-Based Solution to Spatio-Temporal Action Detection in Untrimmed Videos,” in IEEE Workshop/Winter Conference on Applications of Computer Vision, 2018.
[BibTeX] [Link]

@inproceedings{53717843,
title = {A Proposal-Based Solution to Spatio-Temporal Action Detection in Untrimmed Videos},
author = {{Joshua Gleason} and {Rajeev Ranjan} and {S. Schwarcz} and {C. Castillo} and {Jun-Cheng Chen} and {R. Chellappa}},
year = 2018,
month = {11},
booktitle = {IEEE Workshop/Winter Conference on Applications of Computer Vision},
url = {https://www.semanticscholar.org/paper/1a2e40b8ef509ed099bb7e77862ed5ddca52c3a2},
}

Maneet Singh, Richa Singh, Mayank Vatsa, N. Ratha, and R. Chellappa, “Recognizing Disguised Faces in the Wild,” in IEEE Transactions on Biometrics Behavior and Identity Science, 2018.
[BibTeX] [Link]

@inproceedings{53728928,
title = {Recognizing Disguised Faces in the Wild},
author = {{Maneet Singh} and {Richa Singh} and {Mayank Vatsa} and {N. Ratha} and {R. Chellappa}},
year = 2018,
month = {11},
booktitle = {IEEE Transactions on Biometrics Behavior and Identity Science},
url = {https://www.semanticscholar.org/paper/47b14a600e6728fb964b3cc964433480560142fa},
}

D. Wang and J. Eisner, “Synthetic Data Made to Order: The Case of Parsing,” in Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Brussels, 2018, p. 1325–1337. doi:10.18653/v1/D18-1163
[BibTeX] [Link]

@InProceedings{wang-eisner-2018-emnlp,
aclid = "D18-1163",
doi = "10.18653/v1/D18-1163",
author = "Dingquan Wang and Jason Eisner",
title = "Synthetic Data Made to Order: The Case of Parsing",
booktitle = "Proceedings of the Conference on Empirical Methods in
Natural Language Processing (EMNLP)",
pages = "1325--1337",
year = "2018",
month = nov,
address = "Brussels",
URL = "http://cs.jhu.edu/~jason/papers/#wang-eisner-2018-emnlp",
}

Kate D. Fischl, A. Andreou, T. Stewart, and Kaitlin L. Fair, “Implementation of the Neural Engineering Framework on the TrueNorth Neurosynaptic System,” in Biomedical Circuits and Systems Conference, 2018.
[BibTeX] [Link]

@inproceedings{56717992,
title = {Implementation of the Neural Engineering Framework on the TrueNorth Neurosynaptic System},
author = {{Kate D. Fischl} and {A. Andreou} and {T. Stewart} and {Kaitlin L. Fair}},
year = 2018,
month = {10},
booktitle = {Biomedical Circuits and Systems Conference},
url = {https://www.semanticscholar.org/paper/55ce934130d3bd91f2144fb6efbb239c44822216},
}

Jun-Cheng Chen, Wei-An Lin, Jingxiao Zheng, and R. Chellappa, “A Real-Time Multi-Task Single Shot Face Detector,” in International Conference on Information Photonics, 2018.
[BibTeX] [Link]

@inproceedings{52191412,
title = {A Real-Time Multi-Task Single Shot Face Detector},
author = {{Jun-Cheng Chen} and {Wei-An Lin} and {Jingxiao Zheng} and {R. Chellappa}},
year = 2018,
month = {10},
booktitle = {International Conference on Information Photonics},
url = {https://www.semanticscholar.org/paper/6043070c2f2f592601e90d2c71dc6fafca48056b},
}

Cheng-I Lai, A. Abad, Korin Richmond, J. Yamagishi, N. Dehak, and Simon King, “Attentive Filtering Networks for Audio Replay Attack Detection,” in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2018.
[BibTeX] [Link]

@inproceedings{53109997,
title = {Attentive Filtering Networks for Audio Replay Attack Detection},
author = {{Cheng-I Lai} and {A. Abad} and {Korin Richmond} and {J. Yamagishi} and {N. Dehak} and {Simon King}},
year = 2018,
month = {10},
booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
url = {https://www.semanticscholar.org/paper/f9a8ffe3778f4962de63d1153d5041722a7eba81},
}

B. Thompson, H. Khayrallah, A. Anastasopoulos, A. D. McCarthy, K. Duh, R. Marvin, P. McNamee, J. Gwinnup, T. Anderson, and P. Koehn, “Freezing Subnetworks to Analyze Domain Adaptation in Neural Machine Translation,” in Proceedings of the Third Conference on Machine Translation: Research Papers, Brussels, Belgium, 2018, p. 124–132. doi:10.18653/v1/W18-6313
[BibTeX] [Abstract] [Link]

To better understand the effectiveness of continued training, we analyze the major components of a neural machine translation system (the encoder, decoder, and each embedding space) and consider each component{‘}s contribution to, and capacity for, domain adaptation. We find that freezing any single component during continued training has minimal impact on performance, and that performance is surprisingly good when a single component is adapted while holding the rest of the model fixed. We also find that continued training does not move the model very far from the out-of-domain model, compared to a sensitivity analysis metric, suggesting that the out-of-domain model can provide a good generic initialization for the new domain.

@inproceedings{thompson-etal-2018-freezing,
title = "Freezing Subnetworks to Analyze Domain Adaptation in Neural Machine Translation",
author = "Thompson, Brian and
Khayrallah, Huda and
Anastasopoulos, Antonios and
McCarthy, Arya D. and
Duh, Kevin and
Marvin, Rebecca and
McNamee, Paul and
Gwinnup, Jeremy and
Anderson, Tim and
Koehn, Philipp",
editor = "Bojar, Ond{\v{r}}ej and
Chatterjee, Rajen and
Federmann, Christian and
Fishel, Mark and
Graham, Yvette and
Haddow, Barry and
Huck, Matthias and
Yepes, Antonio Jimeno and
Koehn, Philipp and
Monz, Christof and
Negri, Matteo and
N{\'e}v{\'e}ol, Aur{\'e}lie and
Neves, Mariana and
Post, Matt and
Specia, Lucia and
Turchi, Marco and
Verspoor, Karin",
booktitle = "Proceedings of the Third Conference on Machine Translation: Research Papers",
month = oct,
year = "2018",
address = "Brussels, Belgium",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-6313",
doi = "10.18653/v1/W18-6313",
pages = "124--132",
abstract = "To better understand the effectiveness of continued training, we analyze the major components of a neural machine translation system (the encoder, decoder, and each embedding space) and consider each component{'}s contribution to, and capacity for, domain adaptation. We find that freezing any single component during continued training has minimal impact on performance, and that performance is surprisingly good when a single component is adapted while holding the rest of the model fixed. We also find that continued training does not move the model very far from the out-of-domain model, compared to a sensitivity analysis metric, suggesting that the out-of-domain model can provide a good generic initialization for the new domain.",
}

P. Koehn, K. Duh, and B. Thompson, “The JHU Machine Translation Systems for WMT 2018,” in Proceedings of the Third Conference on Machine Translation: Shared Task Papers, Belgium, Brussels, 2018, p. 438–444. doi:10.18653/v1/W18-6417
[BibTeX] [Abstract] [Link]

We report on the efforts of the Johns Hopkins University to develop neural machine translation systems for the shared task for news translation organized around the Conference for Machine Translation (WMT) 2018. We developed systems for German{–}English, English{–} German, and Russian{–}English. Our novel contributions are iterative back-translation and fine-tuning on test sets from prior years.

@inproceedings{koehn-etal-2018-jhu,
title = "The {JHU} Machine Translation Systems for {WMT} 2018",
author = "Koehn, Philipp and
Duh, Kevin and
Thompson, Brian",
editor = "Bojar, Ond{\v{r}}ej and
Chatterjee, Rajen and
Federmann, Christian and
Fishel, Mark and
Graham, Yvette and
Haddow, Barry and
Huck, Matthias and
Yepes, Antonio Jimeno and
Koehn, Philipp and
Monz, Christof and
Negri, Matteo and
N{\'e}v{\'e}ol, Aur{\'e}lie and
Neves, Mariana and
Post, Matt and
Specia, Lucia and
Turchi, Marco and
Verspoor, Karin",
booktitle = "Proceedings of the Third Conference on Machine Translation: Shared Task Papers",
month = oct,
year = "2018",
address = "Belgium, Brussels",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-6417",
doi = "10.18653/v1/W18-6417",
pages = "438--444",
abstract = "We report on the efforts of the Johns Hopkins University to develop neural machine translation systems for the shared task for news translation organized around the Conference for Machine Translation (WMT) 2018. We developed systems for German{--}English, English{--} German, and Russian{--}English. Our novel contributions are iterative back-translation and fine-tuning on test sets from prior years.",
}

Sheng Zhang, Xiaodong Liu, Jingjing Liu, Jianfeng Gao, Kevin Duh, and Benjamin Van Durme, “ReCoRD: Bridging the Gap between Human and Machine Commonsense Reading Comprehension,” in arXiv.org, 2018.
[BibTeX] [Link]

@inproceedings{53116244,
title = {ReCoRD: Bridging the Gap between Human and Machine Commonsense Reading Comprehension},
author = {{Sheng Zhang} and {Xiaodong Liu} and {Jingjing Liu} and {Jianfeng Gao} and {Kevin Duh} and {Benjamin Van Durme}},
year = 2018,
month = {10},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/a5b66ee341cb990f7f70a124b5fab3316d3b7e27},
}

K.P. Subbalakshmi, A. Galstyan, R. Chellappa, and Charles Clancy, “Sensemaking Research Roadmap.” 2018.
[BibTeX] [Link]

@inproceedings{69464873,
title = {Sensemaking Research Roadmap},
author = {{K.P. Subbalakshmi} and {A. Galstyan} and {R. Chellappa} and {Charles Clancy}},
year = 2018,
month = {10},
booktitle = {},
url = {https://www.semanticscholar.org/paper/d93c6b12d5b2131dd196c790abc1135c9b6ffcab},
}

Christos Sapsanis, Nathaniel Welsh, Michael Pozin, Guillaume Garreau, Gaspar Tognetti, Hani Bakhshaee, P. Pouliquen, R. Mittal, W. R. Thompson, and A. Andreou, “StethoVest: A simultaneous multichannel wearable system for cardiac acoustic mapping,” in Biomedical Circuits and Systems Conference, 2018.
[BibTeX] [Link]

@inproceedings{56717729,
title = {StethoVest: A simultaneous multichannel wearable system for cardiac acoustic mapping},
author = {{Christos Sapsanis} and {Nathaniel Welsh} and {Michael Pozin} and {Guillaume Garreau} and {Gaspar Tognetti} and {Hani Bakhshaee} and {P. Pouliquen} and {R. Mittal} and {W. R. Thompson} and {A. Andreou}},
year = 2018,
month = {10},
booktitle = {Biomedical Circuits and Systems Conference},
url = {https://www.semanticscholar.org/paper/f0f1d49a014881e74de58f328db3a54aae6863b9},
}

Daniel R. Mendat, A. Cassidy, Guido Zarrella, and A. Andreou, “Word2vec Word Similarities on IBM’s TrueNorth Neurosynaptic System,” in Biomedical Circuits and Systems Conference, 2018.
[BibTeX] [Link]

@inproceedings{56717891,
title = {Word2vec Word Similarities on IBM's TrueNorth Neurosynaptic System},
author = {{Daniel R. Mendat} and {A. Cassidy} and {Guido Zarrella} and {A. Andreou}},
year = 2018,
month = {10},
booktitle = {Biomedical Circuits and Systems Conference},
url = {https://www.semanticscholar.org/paper/f185dbbf55b2229aecf82f486550a2f9d71be1d4},
}

R. Cotterell, C. Kirov, John Sylak-Glassman, G. Walther, Ekaterina Vylomova, A. D. McCarthy, K. Kann, S. Mielke, G. Nicolai, Miikka Silfverberg, D. Yarowsky, J. Eisner, and M. Hulden, “The CoNLL–SIGMORPHON 2018 Shared Task: Universal Morphological Reinflection,” in Proceedings of the CoNLL SIGMORPHON 2018 Shared Task: Universal Morphological Reinflection, Brussels, 2018, p. 1–27. doi:10.18653/v1/K18-3001
[BibTeX] [Link]

@InProceedings{cotterell-et-al-2018-shared,
aclid = "K18-3001",
doi = "10.18653/v1/K18-3001",
author = "Ryan Cotterell and Christo Kirov and John
Sylak-Glassman and G{\'e}raldine Walther and Ekaterina
Vylomova and Arya D. McCarthy and Katharina Kann and
Sabrina Mielke and Garrett Nicolai and Miikka
Silfverberg and David Yarowsky and Jason Eisner and
Mans Hulden",
title = "The {CoNLL}--{SIGMORPHON} 2018 Shared Task: Universal
Morphological Reinflection",
booktitle = "Proceedings of the CoNLL SIGMORPHON 2018 Shared Task:
Universal Morphological Reinflection",
pages = "1--27",
year = "2018",
month = oct,
address = "Brussels",
URL = "http://cs.jhu.edu/~jason/papers/#cotterell-et-al-2018-shared",
}

H. Khayrallah, B. Thompson, K. Duh, and P. Koehn, “Regularized Training Objective for Continued Training for Domain Adaptation in Neural Machine Translation,” in Proceedings of the 2nd Workshop on Neural Machine Translation and Generation, Melbourne, Australia, 2018, p. 36–44. doi:10.18653/v1/W18-2705
[BibTeX] [Abstract] [Link]

Supervised domain adaptation{–-}where a large generic corpus and a smaller in-domain corpus are both available for training{–-}is a challenge for neural machine translation (NMT). Standard practice is to train a generic model and use it to initialize a second model, then continue training the second model on in-domain data to produce an in-domain model. We add an auxiliary term to the training objective during continued training that minimizes the cross entropy between the in-domain model{‘}s output word distribution and that of the out-of-domain model to prevent the model{‘}s output from differing too much from the original out-of-domain model. We perform experiments on EMEA (descriptions of medicines) and TED (rehearsed presentations), initialized from a general domain (WMT) model. Our method shows improvements over standard continued training by up to 1.5 BLEU.

@inproceedings{khayrallah-etal-2018-regularized,
title = "Regularized Training Objective for Continued Training for Domain Adaptation in Neural Machine Translation",
author = "Khayrallah, Huda and
Thompson, Brian and
Duh, Kevin and
Koehn, Philipp",
editor = "Birch, Alexandra and
Finch, Andrew and
Luong, Thang and
Neubig, Graham and
Oda, Yusuke",
booktitle = "Proceedings of the 2nd Workshop on Neural Machine Translation and Generation",
month = jul,
year = "2018",
address = "Melbourne, Australia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-2705",
doi = "10.18653/v1/W18-2705",
pages = "36--44",
abstract = "Supervised domain adaptation{---}where a large generic corpus and a smaller in-domain corpus are both available for training{---}is a challenge for neural machine translation (NMT). Standard practice is to train a generic model and use it to initialize a second model, then continue training the second model on in-domain data to produce an in-domain model. We add an auxiliary term to the training objective during continued training that minimizes the cross entropy between the in-domain model{'}s output word distribution and that of the out-of-domain model to prevent the model{'}s output from differing too much from the original out-of-domain model. We perform experiments on EMEA (descriptions of medicines) and TED (rehearsed presentations), initialized from a general domain (WMT) model. Our method shows improvements over standard continued training by up to 1.5 BLEU.",
}

X. Liu, Y. Shen, K. Duh, and J. Gao, “Stochastic Answer Networks for Machine Reading Comprehension,” in Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Melbourne, Australia, 2018, p. 1694–1704. doi:10.18653/v1/P18-1157
[BibTeX] [Abstract] [Link]

We propose a simple yet robust stochastic answer network (SAN) that simulates multi-step reasoning in machine reading comprehension. Compared to previous work such as ReasoNet which used reinforcement learning to determine the number of steps, the unique feature is the use of a kind of stochastic prediction dropout on the answer module (final layer) of the neural network during the training. We show that this simple trick improves robustness and achieves results competitive to the state-of-the-art on the Stanford Question Answering Dataset (SQuAD), the Adversarial SQuAD, and the Microsoft MAchine Reading COmprehension Dataset (MS MARCO).

@inproceedings{liu-etal-2018-stochastic,
title = "Stochastic Answer Networks for Machine Reading Comprehension",
author = "Liu, Xiaodong and
Shen, Yelong and
Duh, Kevin and
Gao, Jianfeng",
editor = "Gurevych, Iryna and
Miyao, Yusuke",
booktitle = "Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = jul,
year = "2018",
address = "Melbourne, Australia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P18-1157",
doi = "10.18653/v1/P18-1157",
pages = "1694--1704",
abstract = "We propose a simple yet robust stochastic answer network (SAN) that simulates multi-step reasoning in machine reading comprehension. Compared to previous work such as ReasoNet which used reinforcement learning to determine the number of steps, the unique feature is the use of a kind of stochastic prediction dropout on the answer module (final layer) of the neural network during the training. We show that this simple trick improves robustness and achieves results competitive to the state-of-the-art on the Stanford Question Answering Dataset (SQuAD), the Adversarial SQuAD, and the Microsoft MAchine Reading COmprehension Dataset (MS MARCO).",
}

S. Zhang, K. Duh, and B. Van Durme, “Fine-grained Entity Typing through Increased Discourse Context and Adaptive Classification Thresholds,” in Proceedings of the Seventh Joint Conference on Lexical and Computational Semantics, New Orleans, Louisiana, 2018, p. 173–179. doi:10.18653/v1/S18-2022
[BibTeX] [Abstract] [Link]

Fine-grained entity typing is the task of assigning fine-grained semantic types to entity mentions. We propose a neural architecture which learns a distributional semantic representation that leverages a greater amount of semantic context {–} both document and sentence level information {–} than prior work. We find that additional context improves performance, with further improvements gained by utilizing adaptive classification thresholds. Experiments show that our approach without reliance on hand-crafted features achieves the state-of-the-art results on three benchmark datasets.

@inproceedings{zhang-etal-2018-fine,
title = "Fine-grained Entity Typing through Increased Discourse Context and Adaptive Classification Thresholds",
author = "Zhang, Sheng and
Duh, Kevin and
Van Durme, Benjamin",
editor = "Nissim, Malvina and
Berant, Jonathan and
Lenci, Alessandro",
booktitle = "Proceedings of the Seventh Joint Conference on Lexical and Computational Semantics",
month = jun,
year = "2018",
address = "New Orleans, Louisiana",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/S18-2022",
doi = "10.18653/v1/S18-2022",
pages = "173--179",
abstract = "Fine-grained entity typing is the task of assigning fine-grained semantic types to entity mentions. We propose a neural architecture which learns a distributional semantic representation that leverages a greater amount of semantic context {--} both document and sentence level information {--} than prior work. We find that additional context improves performance, with further improvements gained by utilizing adaptive classification thresholds. Experiments show that our approach without reliance on hand-crafted features achieves the state-of-the-art results on three benchmark datasets.",
}

A. Benton and M. Dredze, “Deep Dirichlet Multinomial Regression,” in Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), New Orleans, Louisiana, 2018, p. 365–374. doi:10.18653/v1/N18-1034
[BibTeX] [Abstract] [Link]

Dirichlet Multinomial Regression (DMR) and other supervised topic models can incorporate arbitrary document-level features to inform topic priors. However, their ability to model corpora are limited by the representation and selection of these features {–} a choice the topic modeler must make. Instead, we seek models that can learn the feature representations upon which to condition topic selection. We present deep Dirichlet Multinomial Regression (dDMR), a generative topic model that simultaneously learns document feature representations and topics. We evaluate dDMR on three datasets: New York Times articles with fine-grained tags, Amazon product reviews with product images, and Reddit posts with subreddit identity. dDMR learns representations that outperform DMR and LDA according to heldout perplexity and are more effective at downstream predictive tasks as the number of topics grows. Additionally, human subjects judge dDMR topics as being more representative of associated document features. Finally, we find that supervision leads to faster convergence as compared to an LDA baseline and that dDMR{‘}s model fit is less sensitive to training parameters than DMR.

@inproceedings{benton-dredze-2018-deep,
title = "Deep {D}irichlet Multinomial Regression",
author = "Benton, Adrian and
Dredze, Mark",
editor = "Walker, Marilyn and
Ji, Heng and
Stent, Amanda",
booktitle = "Proceedings of the 2018 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)",
month = jun,
year = "2018",
address = "New Orleans, Louisiana",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N18-1034",
doi = "10.18653/v1/N18-1034",
pages = "365--374",
abstract = "Dirichlet Multinomial Regression (DMR) and other supervised topic models can incorporate arbitrary document-level features to inform topic priors. However, their ability to model corpora are limited by the representation and selection of these features {--} a choice the topic modeler must make. Instead, we seek models that can learn the feature representations upon which to condition topic selection. We present deep Dirichlet Multinomial Regression (dDMR), a generative topic model that simultaneously learns document feature representations and topics. We evaluate dDMR on three datasets: New York Times articles with fine-grained tags, Amazon product reviews with product images, and Reddit posts with subreddit identity. dDMR learns representations that outperform DMR and LDA according to heldout perplexity and are more effective at downstream predictive tasks as the number of topics grows. Additionally, human subjects judge dDMR topics as being more representative of associated document features. Finally, we find that supervision leads to faster convergence as compared to an LDA baseline and that dDMR{'}s model fit is less sensitive to training parameters than DMR.",
}

S. Sasaki, S. Sun, S. Schamoni, K. Duh, and K. Inui, “Cross-Lingual Learning-to-Rank with Shared Representations,” in Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers), New Orleans, Louisiana, 2018, p. 458–463. doi:10.18653/v1/N18-2073
[BibTeX] [Abstract] [Link]

Cross-lingual information retrieval (CLIR) is a document retrieval task where the documents are written in a language different from that of the user{‘}s query. This is a challenging problem for data-driven approaches due to the general lack of labeled training data. We introduce a large-scale dataset derived from Wikipedia to support CLIR research in 25 languages. Further, we present a simple yet effective neural learning-to-rank model that shares representations across languages and reduces the data requirement. This model can exploit training data in, for example, Japanese-English CLIR to improve the results of Swahili-English CLIR.

@inproceedings{sasaki-etal-2018-cross,
title = "Cross-Lingual Learning-to-Rank with Shared Representations",
author = "Sasaki, Shota and
Sun, Shuo and
Schamoni, Shigehiko and
Duh, Kevin and
Inui, Kentaro",
editor = "Walker, Marilyn and
Ji, Heng and
Stent, Amanda",
booktitle = "Proceedings of the 2018 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)",
month = jun,
year = "2018",
address = "New Orleans, Louisiana",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N18-2073",
doi = "10.18653/v1/N18-2073",
pages = "458--463",
abstract = "Cross-lingual information retrieval (CLIR) is a document retrieval task where the documents are written in a language different from that of the user{'}s query. This is a challenging problem for data-driven approaches due to the general lack of labeled training data. We introduce a large-scale dataset derived from Wikipedia to support CLIR research in 25 languages. Further, we present a simple yet effective neural learning-to-rank model that shares representations across languages and reduces the data requirement. This model can exploit training data in, for example, Japanese-English CLIR to improve the results of Swahili-English CLIR.",
}

Z. Wood-Doughty, P. Mahajan, and M. Dredze, “Johns Hopkins or johnny-hopkins: Classifying Individuals versus Organizations on Twitter,” in Proceedings of the Second Workshop on Computational Modeling of People’s Opinions, Personality, and Emotions in Social Media, New Orleans, Louisiana, USA, 2018, p. 56–61. doi:10.18653/v1/W18-1108
[BibTeX] [Abstract] [Link]

Twitter user accounts include a range of different user types. While many individuals use Twitter, organizations also have Twitter accounts. Identifying opinions and trends from Twitter requires the accurate differentiation of these two groups. Previous work (McCorriston et al., 2015) presented a method for determining if an account was an individual or organization based on account profile and a collection of tweets. We present a method that relies solely on the account profile, allowing for the classification of individuals versus organizations based on a single tweet. Our method obtains accuracies comparable to methods that rely on much more information by leveraging two improvements: a character-based Convolutional Neural Network, and an automatically derived labeled corpus an order of magnitude larger than the previously available dataset. We make both the dataset and the resulting tool available.

@inproceedings{wood-doughty-etal-2018-johns,
title = "{J}ohns {H}opkins or johnny-hopkins: Classifying Individuals versus Organizations on {T}witter",
author = "Wood-Doughty, Zach and
Mahajan, Praateek and
Dredze, Mark",
editor = "Nissim, Malvina and
Patti, Viviana and
Plank, Barbara and
Wagner, Claudia",
booktitle = "Proceedings of the Second Workshop on Computational Modeling of People{'}s Opinions, Personality, and Emotions in Social Media",
month = jun,
year = "2018",
address = "New Orleans, Louisiana, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-1108",
doi = "10.18653/v1/W18-1108",
pages = "56--61",
abstract = "Twitter user accounts include a range of different user types. While many individuals use Twitter, organizations also have Twitter accounts. Identifying opinions and trends from Twitter requires the accurate differentiation of these two groups. Previous work (McCorriston et al., 2015) presented a method for determining if an account was an individual or organization based on account profile and a collection of tweets. We present a method that relies solely on the account profile, allowing for the classification of individuals versus organizations based on a single tweet. Our method obtains accuracies comparable to methods that rely on much more information by leveraging two improvements: a character-based Convolutional Neural Network, and an automatically derived labeled corpus an order of magnitude larger than the previously available dataset. We make both the dataset and the resulting tool available.",
}

P. Shapiro and K. Duh, “Morphological Word Embeddings for Arabic Neural Machine Translation in Low-Resource Settings,” in Proceedings of the Second Workshop on Subword/Character LEvel Models, New Orleans, 2018, p. 1–11. doi:10.18653/v1/W18-1201
[BibTeX] [Abstract] [Link]

Neural machine translation has achieved impressive results in the last few years, but its success has been limited to settings with large amounts of parallel data. One way to improve NMT for lower-resource settings is to initialize a word-based NMT model with pretrained word embeddings. However, rare words still suffer from lower quality word embeddings when trained with standard word-level objectives. We introduce word embeddings that utilize morphological resources, and compare to purely unsupervised alternatives. We work with Arabic, a morphologically rich language with available linguistic resources, and perform Ar-to-En MT experiments on a small corpus of TED subtitles. We find that word embeddings utilizing subword information consistently outperform standard word embeddings on a word similarity task and as initialization of the source word embeddings in a low-resource NMT system.

@inproceedings{shapiro-duh-2018-morphological,
title = "Morphological Word Embeddings for {A}rabic Neural Machine Translation in Low-Resource Settings",
author = "Shapiro, Pamela and
Duh, Kevin",
editor = {Faruqui, Manaal and
Sch{\"u}tze, Hinrich and
Trancoso, Isabel and
Tsvetkov, Yulia and
Yaghoobzadeh, Yadollah},
booktitle = "Proceedings of the Second Workshop on Subword/Character {LE}vel Models",
month = jun,
year = "2018",
address = "New Orleans",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-1201",
doi = "10.18653/v1/W18-1201",
pages = "1--11",
abstract = "Neural machine translation has achieved impressive results in the last few years, but its success has been limited to settings with large amounts of parallel data. One way to improve NMT for lower-resource settings is to initialize a word-based NMT model with pretrained word embeddings. However, rare words still suffer from lower quality word embeddings when trained with standard word-level objectives. We introduce word embeddings that utilize morphological resources, and compare to purely unsupervised alternatives. We work with Arabic, a morphologically rich language with available linguistic resources, and perform Ar-to-En MT experiments on a small corpus of TED subtitles. We find that word embeddings utilizing subword information consistently outperform standard word embeddings on a word similarity task and as initialization of the source word embeddings in a low-resource NMT system.",
}

H. Mei, S. Zhang, K. Duh, and B. Van Durme, “Halo: Learning Semantics-Aware Representations for Cross-Lingual Information Extraction,” in Proceedings of the Seventh Joint Conference on Lexical and Computational Semantics, New Orleans, Louisiana, 2018, p. 142–147. doi:10.18653/v1/S18-2017
[BibTeX] [Abstract] [Link]

Cross-lingual information extraction (CLIE) is an important and challenging task, especially in low resource scenarios. To tackle this challenge, we propose a training method, called \textit{Halo}, which enforces the local region of each hidden state of a neural model to only generate target tokens with the same semantic structure tag. This simple but powerful technique enables a neural model to learn semantics-aware representations that are robust to noise, without introducing any extra parameter, thus yielding better generalization in both high and low resource settings.

@inproceedings{mei-etal-2018-halo,
title = "{H}alo: Learning Semantics-Aware Representations for Cross-Lingual Information Extraction",
author = "Mei, Hongyuan and
Zhang, Sheng and
Duh, Kevin and
Van Durme, Benjamin",
editor = "Nissim, Malvina and
Berant, Jonathan and
Lenci, Alessandro",
booktitle = "Proceedings of the Seventh Joint Conference on Lexical and Computational Semantics",
month = jun,
year = "2018",
address = "New Orleans, Louisiana",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/S18-2017",
doi = "10.18653/v1/S18-2017",
pages = "142--147",
abstract = "Cross-lingual information extraction (CLIE) is an important and challenging task, especially in low resource scenarios. To tackle this challenge, we propose a training method, called \textit{Halo}, which enforces the local region of each hidden state of a neural model to only generate target tokens with the same semantic structure tag. This simple but powerful technique enables a neural model to learn semantics-aware representations that are robust to noise, without introducing any extra parameter, thus yielding better generalization in both high and low resource settings.",
}

Z. Wood-Doughty, N. Andrews, R. Marvin, and M. Dredze, “Predicting Twitter User Demographics from Names Alone,” in Proceedings of the Second Workshop on Computational Modeling of People’s Opinions, Personality, and Emotions in Social Media, New Orleans, Louisiana, USA, 2018, p. 105–111. doi:10.18653/v1/W18-1114
[BibTeX] [Abstract] [Link]

Social media analysis frequently requires tools that can automatically infer demographics to contextualize trends. These tools often require hundreds of user-authored messages for each user, which may be prohibitive to obtain when analyzing millions of users. We explore character-level neural models that learn a representation of a user{‘}s name and screen name to predict gender and ethnicity, allowing for demographic inference with minimal data. We release trained models1 which may enable new demographic analyses that would otherwise require enormous amounts of data collection

@inproceedings{wood-doughty-etal-2018-predicting,
title = "Predicting {T}witter User Demographics from Names Alone",
author = "Wood-Doughty, Zach and
Andrews, Nicholas and
Marvin, Rebecca and
Dredze, Mark",
editor = "Nissim, Malvina and
Patti, Viviana and
Plank, Barbara and
Wagner, Claudia",
booktitle = "Proceedings of the Second Workshop on Computational Modeling of People{'}s Opinions, Personality, and Emotions in Social Media",
month = jun,
year = "2018",
address = "New Orleans, Louisiana, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-1114",
doi = "10.18653/v1/W18-1114",
pages = "105--111",
abstract = "Social media analysis frequently requires tools that can automatically infer demographics to contextualize trends. These tools often require hundreds of user-authored messages for each user, which may be prohibitive to obtain when analyzing millions of users. We explore character-level neural models that learn a representation of a user{'}s name and screen name to predict gender and ethnicity, allowing for demographic inference with minimal data. We release trained models1 which may enable new demographic analyses that would otherwise require enormous amounts of data collection",
}

R. Cotterell, C. Kirov, S. J. Mielke, and J. Eisner, “Unsupervised Disambiguation of Syncretism in Inflected Lexicons,” in Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT), New Orleans, 2018, p. 548–553. doi:10.18653/v1/N18-2087
[BibTeX] [Link]

@InProceedings{cotterell-et-al-2018-syncretism,
aclid = "N18-2087",
doi = "10.18653/v1/N18-2087",
author = "Ryan Cotterell and Christo Kirov and Sabrina J. Mielke
and Jason Eisner",
title = "Unsupervised Disambiguation of Syncretism in Inflected
Lexicons",
booktitle = "Proceedings of the 2018 Conference of the North
American Chapter of the Association for Computational
Linguistics: Human Language Technologies (NAACL-HLT)",
pages = "548--553",
year = "2018",
month = jun,
address = "New Orleans",
URL = "http://cs.jhu.edu/~jason/papers/#cotterell-et-al-2018-syncretism",
}

R. Cotterell, S. J. Mielke, J. Eisner, and B. Roark, “Are All Languages Equally Hard to Language-Model?,” in Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT), New Orleans, 2018, p. 536–541. doi:10.18653/v1/N18-2085
[BibTeX] [Link]

@InProceedings{cotterell-et-al-2018-lm,
aclid = "N18-2085",
doi = "10.18653/v1/N18-2085",
author = "Ryan Cotterell and Sabrina J. Mielke and Jason Eisner
and Brian Roark",
title = "Are All Languages Equally Hard to Language-Model?",
booktitle = "Proceedings of the 2018 Conference of the North
American Chapter of the Association for Computational
Linguistics: Human Language Technologies (NAACL-HLT)",
pages = "536--541",
year = "2018",
month = jun,
address = "New Orleans",
URL = "http://cs.jhu.edu/~jason/papers/#cotterell-et-al-2018-lm",
}

C. Lin and J. Eisner, “Neural Particle Smoothing for Sampling from Conditional Sequence Models,” in Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT), New Orleans, 2018, p. 929–941. doi:10.18653/v1/N18-1085
[BibTeX] [Link]

@InProceedings{lin-eisner-2018-naacl,
aclid = "N18-1085",
doi = "10.18653/v1/N18-1085",
author = "Chu-Cheng Lin and Jason Eisner",
title = "Neural Particle Smoothing for Sampling from
Conditional Sequence Models",
booktitle = "Proceedings of the 2018 Conference of the North
American Chapter of the Association for Computational
Linguistics: Human Language Technologies (NAACL-HLT)",
pages = "929--941",
year = "2018",
month = jun,
address = "New Orleans",
URL = "http://cs.jhu.edu/~jason/papers/#lin-eisner-2018-naacl",
}

R. Cotterell and J. Eisner, “A Deep Generative Model of Vowel Formant Typology,” in Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT), New Orleans, 2018, p. 37–46. doi:10.18653/v1/N18-1004
[BibTeX] [Link]

@InProceedings{cotterell-eisner-2018-naacl,
aclid = "N18-1004",
doi = "10.18653/v1/N18-1004",
author = "Ryan Cotterell and Jason Eisner",
title = "A Deep Generative Model of Vowel Formant Typology",
booktitle = "Proceedings of the 2018 Conference of the North
American Chapter of the Association for Computational
Linguistics: Human Language Technologies (NAACL-HLT)",
pages = "37--46",
year = "2018",
month = jun,
address = "New Orleans",
URL = "http://cs.jhu.edu/~jason/papers/#cotterell-eisner-2018-naacl",
}

C. Kirov, R. Cotterell, S. -, G. Walther, E. Vylomova, P. Xia, M. Faruqui, S. J. Mielke, A. D. McCarthy, Sandra Kübler, D. Yarowsky, J. Eisner, and M. Hulden, “UniMorph 2.0: Universal Morphology,” in Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018), Miyazaki, Japan, 2018.
[BibTeX] [Link]

@InProceedings{UNIMORPH-2018,
author = "Christo Kirov and Ryan Cotterell and John
Sylak{-}Glassman and G{\'{e}}raldine Walther and
Ekaterina Vylomova and Patrick Xia and Manaal Faruqui
and Sabrina J. Mielke and Arya D. McCarthy and Sandra
K{\"{u}}bler and David Yarowsky and Jason Eisner and
Mans Hulden",
title = "{UniMorph} 2.0: Universal Morphology",
booktitle = "Proceedings of the Eleventh International Conference
on Language Resources and Evaluation (LREC 2018)",
year = "2018",
month = may,
address = "Miyazaki, Japan",
URL = "http://cs.jhu.edu/~jason/papers/#UNIMORPH-2018",
}

J. Eisner and N. W. Filardo, “Treating Machine Learning Algorithms as Declaratively Specified Circuits,” in Proceedings of the Conference on Systems and Machine Learning (SysML), Palo Alto, 2018.
[BibTeX] [Link]

@InProceedings{filardo-eisner-2018-sysml,
author = "Jason Eisner and Nathaniel Wesley Filardo",
title = "Treating Machine Learning Algorithms as Declaratively
Specified Circuits",
booktitle = "Proceedings of the Conference on Systems and Machine
Learning (SysML)",
year = "2018",
month = feb,
address = "Palo Alto",
URL = "http://cs.jhu.edu/~jason/papers/#filardo-eisner-2018-sysml",
}

D. Wang and J. Eisner, “Predicting Fine-Grained Syntactic Typology from Surface Features,” in Proceedings of the Society for Computation in Linguistics (SCiL), Salt Lake City, 2018. doi:10.7275/R5F769RV
[BibTeX] [Link]

@InProceedings{wang-eisner-2018-scil,
doi = "10.7275/R5F769RV",
author = "Dingquan Wang and Jason Eisner",
title = "Predicting Fine-Grained Syntactic Typology from
Surface Features",
booktitle = "Proceedings of the Society for Computation in
Linguistics (SCiL)",
year = "2018",
month = jan,
volume = "1",
address = "Salt Lake City",
URL = "http://cs.jhu.edu/~jason/papers/#wang-eisner-2018-scil",
}

R. Cotterell, C. Kirov, M. Hulden, and J. Eisner, “Quantifying the Trade-off Between Two Types of Morphological Complexity,” in Proceedings of the Society for Computation in Linguistics (SCiL), Salt Lake City, 2018, p. 209–210. doi:10.7275/R57P8WK1
[BibTeX] [Link]

@InProceedings{cotterell-et-al-2018-scil,
doi = "10.7275/R57P8WK1",
author = "Ryan Cotterell and Christo Kirov and Mans Hulden and
Jason Eisner",
title = "Quantifying the Trade-off Between Two Types of
Morphological Complexity",
booktitle = "Proceedings of the Society for Computation in
Linguistics (SCiL)",
year = "2018",
month = jan,
volume = "1",
pages = "209--210",
address = "Salt Lake City",
URL = "http://cs.jhu.edu/~jason/papers/#cotterell-et-al-2018-scil",
}

Rajeev Ranjan, Ankan Bansal, Jingxiao Zheng, Hongyu Xu, Joshua Gleason, Boyu Lu, Anirudh Nanduri, Jun-Cheng Chen, C. Castillo, and R. Chellappa, “A Fast and Accurate System for Face Detection, Identification, and Verification,” in IEEE Transactions on Biometrics Behavior and Identity Science, 2018.
[BibTeX] [Link]

@inproceedings{52307053,
title = {A Fast and Accurate System for Face Detection, Identification, and Verification},
author = {{Rajeev Ranjan} and {Ankan Bansal} and {Jingxiao Zheng} and {Hongyu Xu} and {Joshua Gleason} and {Boyu Lu} and {Anirudh Nanduri} and {Jun-Cheng Chen} and {C. Castillo} and {R. Chellappa}},
year = 2018,
month = {9},
booktitle = {IEEE Transactions on Biometrics Behavior and Identity Science},
url = {https://www.semanticscholar.org/paper/8a2deb2b4216f6c065c5e955706ce157d96625a1},
}

Z. Wood-Doughty, I. Shpitser, and M. Dredze, “Challenges of Using Text Classifiers for Causal Inference,” in Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, 2018, p. 4586–4598. doi:10.18653/v1/D18-1488
[BibTeX] [Abstract] [Link]

Causal understanding is essential for many kinds of decision-making, but causal inference from observational data has typically only been applied to structured, low-dimensional datasets. While text classifiers produce low-dimensional outputs, their use in causal inference has not previously been studied. To facilitate causal analyses based on language data, we consider the role that text classifiers can play in causal inference through established modeling mechanisms from the causality literature on missing data and measurement error. We demonstrate how to conduct causal analyses using text classifiers on simulated and Yelp data, and discuss the opportunities and challenges of future work that uses text data in causal inference.

@inproceedings{wood-doughty-etal-2018-challenges,
title = "Challenges of Using Text Classifiers for Causal Inference",
author = "Wood-Doughty, Zach and
Shpitser, Ilya and
Dredze, Mark",
editor = "Riloff, Ellen and
Chiang, David and
Hockenmaier, Julia and
Tsujii, Jun{'}ichi",
booktitle = "Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing",
month = oct # "-" # nov,
year = "2018",
address = "Brussels, Belgium",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D18-1488",
doi = "10.18653/v1/D18-1488",
pages = "4586--4598",
abstract = "Causal understanding is essential for many kinds of decision-making, but causal inference from observational data has typically only been applied to structured, low-dimensional datasets. While text classifiers produce low-dimensional outputs, their use in causal inference has not previously been studied. To facilitate causal analyses based on language data, we consider the role that text classifiers can play in causal inference through established modeling mechanisms from the causality literature on missing data and measurement error. We demonstrate how to conduct causal analyses using text classifiers on simulated and Yelp data, and discuss the opportunities and challenges of future work that uses text data in causal inference.",
}

Y. Balaji, Hamed Hassani, R. Chellappa, and S. Feizi, “Entropic GANs meet VAEs: A Statistical Approach to Compute Sample Likelihoods in GANs,” in International Conference on Machine Learning, 2018.
[BibTeX] [Link]

@inproceedings{52947374,
title = {Entropic GANs meet VAEs: A Statistical Approach to Compute Sample Likelihoods in GANs},
author = {{Y. Balaji} and {Hamed Hassani} and {R. Chellappa} and {S. Feizi}},
year = 2018,
month = {9},
booktitle = {International Conference on Machine Learning},
url = {https://www.semanticscholar.org/paper/e8d2ad861e4d107ae2c0d1b7bb053d06022dfe1c},
}

Ning Gao, Mark Dredze, and Douglas W. Oard, “Enhancing Scientific Collaboration Through Knowledge Base Population and Linking for Meetings,” in Hawaii International Conference on System Sciences, 2018.
[BibTeX] [Link]

@inproceedings{38114028,
title = {Enhancing Scientific Collaboration Through Knowledge Base Population and Linking for Meetings},
author = {{Ning Gao} and {Mark Dredze} and {Douglas W. Oard}},
year = 2018,
month = {1},
booktitle = {Hawaii International Conference on System Sciences},
url = {https://www.semanticscholar.org/paper/7240c4e11f30827cca6e35cd12396b572bf24685},
}

Kayode A. Sanni, Tomas Figliolia, Gaspar Tognetti, P. Pouliquen, and A. Andreou, “A Charge-Based Architecture for Energy-Efficient Vector-Vector Multiplication in 65nm CMOS,” in International Symposium on Circuits and Systems, 2018.
[BibTeX] [Link]

@inproceedings{53086238,
title = {A Charge-Based Architecture for Energy-Efficient Vector-Vector Multiplication in 65nm CMOS},
author = {{Kayode A. Sanni} and {Tomas Figliolia} and {Gaspar Tognetti} and {P. Pouliquen} and {A. Andreou}},
year = 2018,
month = {5},
booktitle = {International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/df50e7680d54dc67dc6bd5b24042800abcabb358},
}

Maya Kabkab, Pouya Samangouei, and R. Chellappa, “Task-Aware Compressed Sensing with Generative Adversarial Networks,” in AAAI Conference on Artificial Intelligence, 2018.
[BibTeX] [Link]

@inproceedings{19100258,
title = {Task-Aware Compressed Sensing with Generative Adversarial Networks},
author = {{Maya Kabkab} and {Pouya Samangouei} and {R. Chellappa}},
year = 2018,
month = {2},
booktitle = {AAAI Conference on Artificial Intelligence},
url = {https://www.semanticscholar.org/paper/8f30b061b4aa39fa1f203dbcab7472021f3c0411},
}

Xiaodong Liu, Wei Li, Yuwei Fang, Aerin Kim, Kevin Duh, and Jianfeng Gao, “Stochastic Answer Networks for SQuAD 2.0,” in arXiv.org, 2018.
[BibTeX] [Link]

@inproceedings{52824259,
title = {Stochastic Answer Networks for SQuAD 2.0},
author = {{Xiaodong Liu} and {Wei Li} and {Yuwei Fang} and {Aerin Kim} and {Kevin Duh} and {Jianfeng Gao}},
year = 2018,
month = {9},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/d0095adcaa33bc549e273a824c3b66d92897fad8},
}

Boyu Lu, Jun-Cheng Chen, C. Castillo, and R. Chellappa, “An Experimental Evaluation of Covariates Effects on Unconstrained Face Verification,” in IEEE Transactions on Biometrics Behavior and Identity Science, 2018.
[BibTeX] [Link]

@inproceedings{52017806,
title = {An Experimental Evaluation of Covariates Effects on Unconstrained Face Verification},
author = {{Boyu Lu} and {Jun-Cheng Chen} and {C. Castillo} and {R. Chellappa}},
year = 2018,
month = {8},
booktitle = {IEEE Transactions on Biometrics Behavior and Identity Science},
url = {https://www.semanticscholar.org/paper/8f1abae983acc7123257bece2afd334549dfe94d},
}

Emily M. Hand, C. Castillo, and R. Chellappa, “Doing the Best We Can With What We Have: Multi-Label Balancing With Selective Learning for Attribute Prediction,” in AAAI Conference on Artificial Intelligence, 2018.
[BibTeX] [Link]

@inproceedings{19216053,
title = {Doing the Best We Can With What We Have: Multi-Label Balancing With Selective Learning for Attribute Prediction},
author = {{Emily M. Hand} and {C. Castillo} and {R. Chellappa}},
year = 2018,
month = {4},
booktitle = {AAAI Conference on Artificial Intelligence},
url = {https://www.semanticscholar.org/paper/f36f15e49ce81d13622348bc2e8bfa16ab54aa03},
}

R. Arora, V. Braverman, and Jalaj Upadhyay, “Differentially Private Robust Low-Rank Approximation,” in Neural Information Processing Systems, 2018.
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@inproceedings{54045327,
title = {Differentially Private Robust Low-Rank Approximation},
author = {{R. Arora} and {V. Braverman} and {Jalaj Upadhyay}},
year = 2018,
booktitle = {Neural Information Processing Systems},
url = {https://www.semanticscholar.org/paper/83ef6de2e9fb2d59f18fe19dd7e6386a0513c2c3},
}

Enayat Ullah, Poorya Mianjy, T. V. Marinov, and R. Arora, “Streaming Kernel PCA with \tildeO(\sqrtn) Random Features,” in Neural Information Processing Systems, 2018.
[BibTeX] [Link]

@inproceedings{51908830,
title = {Streaming Kernel PCA with \tilde{O}(\sqrt{n}) Random Features},
author = {{Enayat Ullah} and {Poorya Mianjy} and {T. V. Marinov} and {R. Arora}},
year = 2018,
booktitle = {Neural Information Processing Systems},
url = {https://www.semanticscholar.org/paper/3fe99499b945ad77c3d76875609c7cffbf3e0299},
}

U. Mahbub, Jukka Komulainen, Denzil Ferreira, and R. Chellappa, “Continuous Authentication of Smartphones Based on Application Usage,” in IEEE Transactions on Biometrics Behavior and Identity Science, 2018.
[BibTeX] [Link]

@inproceedings{51967626,
title = {Continuous Authentication of Smartphones Based on Application Usage},
author = {{U. Mahbub} and {Jukka Komulainen} and {Denzil Ferreira} and {R. Chellappa}},
year = 2018,
month = {7},
booktitle = {IEEE Transactions on Biometrics Behavior and Identity Science},
url = {https://www.semanticscholar.org/paper/cc3e70186745b7a2476c8773cf614c294f02f53c},
}

P. S. Nidadavolu, Cheng-I Lai, J. Villalba, and N. Dehak, “Investigation on Bandwidth Extension for Speaker Recognition,” in Interspeech, 2018.
[BibTeX] [Link]

@inproceedings{52192345,
title = {Investigation on Bandwidth Extension for Speaker Recognition},
author = {{P. S. Nidadavolu} and {Cheng-I Lai} and {J. Villalba} and {N. Dehak}},
year = 2018,
month = {9},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/204abd534d69efa728a4c2ff5d1f212431890393},
}

Iskandar Atakhodjaev, B. Bosworth, Brian C. Grubel, M. Kossey, J. Villalba, A. Cooper, N. Dehak, A. Foster, and M. Foster, “Investigation of Deep Learning Attacks on Nonlinear Silicon Photonic PUFs,” in Conference on Lasers and Electro-Optics, 2018.
[BibTeX] [Link]

@inproceedings{51977464,
title = {Investigation of Deep Learning Attacks on Nonlinear Silicon Photonic PUFs},
author = {{Iskandar Atakhodjaev} and {B. Bosworth} and {Brian C. Grubel} and {M. Kossey} and {J. Villalba} and {A. Cooper} and {N. Dehak} and {A. Foster} and {M. Foster}},
year = 2018,
month = {5},
booktitle = {Conference on Lasers and Electro-Optics},
url = {https://www.semanticscholar.org/paper/d8a076181efd0f7a88bb272fc40ac804ac2d7c21},
}

Rajeev Ranjan, S. Sankaranarayanan, Ankan Bansal, Navaneeth Bodla, Jun-Cheng Chen, Vishal M. Patel, C. Castillo, and R. Chellappa, “Deep Learning for Understanding Faces: Machines May Be Just as Good, or Better, than Humans,” in IEEE Signal Processing Magazine, 2018.
[BibTeX] [Link]

@inproceedings{206487084,
title = {Deep Learning for Understanding Faces: Machines May Be Just as Good, or Better, than Humans},
author = {{Rajeev Ranjan} and {S. Sankaranarayanan} and {Ankan Bansal} and {Navaneeth Bodla} and {Jun-Cheng Chen} and {Vishal M. Patel} and {C. Castillo} and {R. Chellappa}},
year = 2018,
month = {1},
booktitle = {IEEE Signal Processing Magazine},
url = {https://www.semanticscholar.org/paper/5a564d108b43c6ff006a86d2fc981cd36c6c54dd},
}

Gregory Sell, Kevin Duh, David Snyder, David Etter, and D. Garcia-Romero, “Audio-Visual Person Recognition in Multimedia Data From the Iarpa Janus Program,” in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2018.
[BibTeX] [Link]

@inproceedings{52287748,
title = {Audio-Visual Person Recognition in Multimedia Data From the Iarpa Janus Program},
author = {{Gregory Sell} and {Kevin Duh} and {David Snyder} and {David Etter} and {D. Garcia-Romero}},
year = 2018,
month = {4},
booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
url = {https://www.semanticscholar.org/paper/4f623e3821d14553b3b286e20910db9225fb723f},
}

Matthew Wiesner, Chunxi Liu, Lucas Ondel, Craig Harman, Vimal Manohar, J. Trmal, Zhongqiang Huang, N. Dehak, and S. Khudanpur, “Automatic Speech Recognition and Topic Identification for Almost-Zero-Resource Languages,” in arXiv: Computation and Language, 2018.
[BibTeX] [Link]

@inproceedings{49309939,
title = {Automatic Speech Recognition and Topic Identification for Almost-Zero-Resource Languages},
author = {{Matthew Wiesner} and {Chunxi Liu} and {Lucas Ondel} and {Craig Harman} and {Vimal Manohar} and {J. Trmal} and {Zhongqiang Huang} and {N. Dehak} and {S. Khudanpur}},
year = 2018,
month = {2},
booktitle = {arXiv: Computation and Language},
url = {https://www.semanticscholar.org/paper/e43de3888fcea68c30559cc3e186ad366ac9daa7},
}

Yuki Lama, Tao Chen, Mark Dredze, Amelia M. Jamison, S. Quinn, and David A. Broniatowski, “Discordance Between Human Papillomavirus Twitter Images and Disparities in Human Papillomavirus Risk and Disease in the United States: Mixed-Methods Analysis,” in Journal of Medical Internet Research, 2018.
[BibTeX] [Link]

@inproceedings{52275517,
title = {Discordance Between Human Papillomavirus Twitter Images and Disparities in Human Papillomavirus Risk and Disease in the United States: Mixed-Methods Analysis},
author = {{Yuki Lama} and {Tao Chen} and {Mark Dredze} and {Amelia M. Jamison} and {S. Quinn} and {David A. Broniatowski}},
year = 2018,
month = {9},
booktitle = {Journal of Medical Internet Research},
url = {https://www.semanticscholar.org/paper/9089dbdeb2b9bb82195f7f893b3c028425c7f36c},
}

Hongyu Xu, Jingjing Zheng, A. Alavi, and R. Chellappa, “Cross-Domain Visual Recognition via Domain Adaptive Dictionary Learning,” in arXiv.org, 2018.
[BibTeX] [Link]

@inproceedings{4881011,
title = {Cross-Domain Visual Recognition via Domain Adaptive Dictionary Learning},
author = {{Hongyu Xu} and {Jingjing Zheng} and {A. Alavi} and {R. Chellappa}},
year = 2018,
month = {4},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/92ec85037f5e195c8aa184534a59b356c6ef7599},
}

Shenmin Zhang, Kevin Duh, and Benjamin Van Durme, “Cross-lingual Semantic Parsing,” in arXiv.org, 2018.
[BibTeX] [Link]

@inproceedings{5054966,
title = {Cross-lingual Semantic Parsing},
author = {{Shenmin Zhang} and {Kevin Duh} and {Benjamin Van Durme}},
year = 2018,
month = {4},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/69ced6c377aadd404893fba6ff36cc004d1e117b},
}

R. Pappagari, J. Villalba, and N. Dehak, “Joint Verification-Identification in end-to-end Multi-Scale CNN Framework for Topic Identification,” in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2018.
[BibTeX] [Link]

@inproceedings{52287820,
title = {Joint Verification-Identification in end-to-end Multi-Scale CNN Framework for Topic Identification},
author = {{R. Pappagari} and {J. Villalba} and {N. Dehak}},
year = 2018,
month = {4},
booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
url = {https://www.semanticscholar.org/paper/298a10dd069404f8846b5f82f46441385e7e4486},
}

Matthew Wiesner, Chunxi Liu, Lucas Ondel, Craig Harman, Vimal Manohar, J. Trmal, Zhongqiang Huang, N. Dehak, and S. Khudanpur, “Automatic Speech Recognition and Topic Identification from Speech for Almost-Zero-Resource Languages,” in Interspeech, 2018.
[BibTeX] [Link]

@inproceedings{52187651,
title = {Automatic Speech Recognition and Topic Identification from Speech for Almost-Zero-Resource Languages},
author = {{Matthew Wiesner} and {Chunxi Liu} and {Lucas Ondel} and {Craig Harman} and {Vimal Manohar} and {J. Trmal} and {Zhongqiang Huang} and {N. Dehak} and {S. Khudanpur}},
year = 2018,
month = {9},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/6a6fe404d780856926dfaabb43120726bccb02e5},
}

L. Moro-Velázquez, Jorge Andrés Gómez García, Juan Ignacio Godino-Llorente, J. Villalba, J. Orozco-Arroyave, and N. Dehak, “Analysis of speaker recognition methodologies and the influence of kinetic changes to automatically detect Parkinson’s Disease,” in Applied Soft Computing, 2018.
[BibTeX] [Link]

@inproceedings{205710736,
title = {Analysis of speaker recognition methodologies and the influence of kinetic changes to automatically detect Parkinson's Disease},
author = {{L. Moro-Velázquez} and {Jorge Andrés Gómez García} and {Juan Ignacio Godino-Llorente} and {J. Villalba} and {J. Orozco-Arroyave} and {N. Dehak}},
year = 2018,
booktitle = {Applied Soft Computing},
url = {https://www.semanticscholar.org/paper/e1ed45247074aafc0fed0b1c7253a3e96785b583},
}

U. Mahbub, Sayantan Sarkar, and R. Chellappa, “Segment-Based Methods for Facial Attribute Detection from Partial Faces,” in IEEE Transactions on Affective Computing, 2018.
[BibTeX] [Link]

@inproceedings{28945696,
title = {Segment-Based Methods for Facial Attribute Detection from Partial Faces},
author = {{U. Mahbub} and {Sayantan Sarkar} and {R. Chellappa}},
year = 2018,
month = {1},
booktitle = {IEEE Transactions on Affective Computing},
url = {https://www.semanticscholar.org/paper/1824ad94533c138d9f424f64a8f17117ba72d74b},
}

Theodore L. Caputi, E. Leas, Mark Dredze, and J. Ayers, “Online Sales of Marijuana: An Unrecognized Public Health Dilemma.,” in American Journal of Preventive Medicine, 2018.
[BibTeX] [Link]

@inproceedings{4340903,
title = {Online Sales of Marijuana: An Unrecognized Public Health Dilemma.},
author = {{Theodore L. Caputi} and {E. Leas} and {Mark Dredze} and {J. Ayers}},
year = 2018,
month = {3},
booktitle = {American Journal of Preventive Medicine},
url = {https://www.semanticscholar.org/paper/67f7bdd965ed18165acc66bef3b04a6bd4cff28d},
}

Thomas S. Murray, Daniel R. Mendat, Kayode A. Sanni, P. Pouliquen, and A. Andreou, “Bio-Inspired Human Action Recognition With a Micro-Doppler Sonar System,” in IEEE Access, 2018.
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@inproceedings{49193444,
title = {Bio-Inspired Human Action Recognition With a Micro-Doppler Sonar System},
author = {{Thomas S. Murray} and {Daniel R. Mendat} and {Kayode A. Sanni} and {P. Pouliquen} and {A. Andreou}},
year = 2018,
booktitle = {IEEE Access},
url = {https://www.semanticscholar.org/paper/f39b7b7af204e9c769653c574284508fc027ce31},
}

Pouya Samangouei, Maya Kabkab, and R. Chellappa, “Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models,” in International Conference on Learning Representations, 2018.
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@inproceedings{3458858,
title = {Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models},
author = {{Pouya Samangouei} and {Maya Kabkab} and {R. Chellappa}},
year = 2018,
month = {2},
booktitle = {International Conference on Learning Representations},
url = {https://www.semanticscholar.org/paper/f7bb1636ced9036b3d0edafc7d82ad43164d41a3},
}

Jaejin Cho, R. Pappagari, Purva Kulkarni, J. Villalba, Yishay Carmiel, and N. Dehak, “Deep Neural Networks for Emotion Recognition Combining Audio and Transcripts,” in Interspeech, 2018.
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@inproceedings{52188103,
title = {Deep Neural Networks for Emotion Recognition Combining Audio and Transcripts},
author = {{Jaejin Cho} and {R. Pappagari} and {Purva Kulkarni} and {J. Villalba} and {Yishay Carmiel} and {N. Dehak}},
year = 2018,
month = {9},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/75b2843539dc8567b1502a19b3788adf6a015eb6},
}

Poorya Mianjy and R. Arora, “Stochastic PCA with (cid:96) 2 and (cid:96) 1 Regularization.” 2018.
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@inproceedings{51868677,
title = {Stochastic PCA with (cid:96) 2 and (cid:96) 1 Regularization},
author = {{Poorya Mianjy} and {R. Arora}},
year = 2018,
booktitle = {},
url = {https://www.semanticscholar.org/paper/23d95f2f7bdb16ceeb35b45348a2ca89ea8330fd},
}

Piotr Żelasko, Piotr Szymański, Jan Mizgajski, Adrian Szymczak, Yishay Carmiel, and N. Dehak, “Punctuation Prediction Model for Conversational Speech,” in Interspeech, 2018.
[BibTeX] [Link]

@inproceedings{49558658,
title = {Punctuation Prediction Model for Conversational Speech},
author = {{Piotr Żelasko} and {Piotr Szymański} and {Jan Mizgajski} and {Adrian Szymczak} and {Yishay Carmiel} and {N. Dehak}},
year = 2018,
month = {7},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/740f94e0325b67e6ff5efba0f5112c977e21a75a},
}

Chunxi Liu, Matthew Wiesner, Shinji Watanabe, Craig Harman, J. Trmal, N. Dehak, and S. Khudanpur, “Low-Resource Contextual Topic Identification on Speech,” in Spoken Language Technology Workshop, 2018.
[BibTeX] [Link]

@inproceedings{49868415,
title = {Low-Resource Contextual Topic Identification on Speech},
author = {{Chunxi Liu} and {Matthew Wiesner} and {Shinji Watanabe} and {Craig Harman} and {J. Trmal} and {N. Dehak} and {S. Khudanpur}},
year = 2018,
month = {7},
booktitle = {Spoken Language Technology Workshop},
url = {https://www.semanticscholar.org/paper/96ed7a7da69d654668b35b50344debd44e87c1a1},
}

David A. Broniatowski, Amelia M. Jamison, SiHua Qi, Lulwah Alkulaib, Tao Chen, Adrian Benton, S. Quinn, and Mark Dredze, “Weaponized Health Communication: Twitter Bots and Russian Trolls Amplify the Vaccine Debate,” in American Journal of Public Health, 2018.
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title = {Weaponized Health Communication: Twitter Bots and Russian Trolls Amplify the Vaccine Debate},
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Nanxin Chen, J. Villalba, Yishay Carmiel, and N. Dehak, “Measuring Uncertainty in Deep Regression Models: The Case of Age Estimation from Speech,” in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2018.
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Mousmita Sarma, Pegah Ghahremani, Daniel Povey, N. Goel, K. K. Sarma, and N. Dehak, “Emotion Identification from Raw Speech Signals Using DNNs,” in Interspeech, 2018.
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Vineet Kushwaha, Maneet Singh, Richa Singh, Mayank Vatsa, N. Ratha, and R. Chellappa, “Disguised Faces in the Wild,” in 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2018.
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Pouya Samangouei, Mahyar Najibi, L. Davis, and R. Chellappa, “Face-MagNet: Magnifying Feature Maps to Detect Small Faces,” in IEEE Workshop/Winter Conference on Applications of Computer Vision, 2018.
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A. O’toole, C. Castillo, Connor J. Parde, Matthew Q. Hill, and R. Chellappa, “Face Space Representations in Deep Convolutional Neural Networks,” in Trends in Cognitive Sciences, 2018.
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G. Stein-O’Brien, R. Arora, A. Culhane, Alexander V. Favorov, L. Garmire, C. Greene, L. Goff, Yifeng Li, Aloune Ngom, M. Ochs, Yanxun Xu, and E. Fertig, “Enter the Matrix: Factorization Uncovers Knowledge from Omics,” in Trends in Genetics, 2018.
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Chris Paxton, Yotam Barnoy, Kapil D. Katyal, R. Arora, and Gregory Hager, “Visual Robot Task Planning,” in IEEE International Conference on Robotics and Automation, 2018.
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Adithya Renduchintala, Pamela Shapiro, Kevin Duh, and Philipp Koehn, “Character-Aware Decoder for Neural Machine Translation,” in arXiv.org, 2018.
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Zhe Wu, Navaneeth Bodla, Bharat Singh, Mahyar Najibi, R. Chellappa, and L. Davis, “Soft Sampling for Robust Object Detection,” in British Machine Vision Conference, 2018.
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Poorya Mianjy and R. Arora, “Stochastic PCA with $\ell_2$ and $\ell_1$ Regularization,” in International Conference on Machine Learning, 2018.
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Rajeev Ranjan, Ankan Bansal, Hongyu Xu, S. Sankaranarayanan, Jun-Cheng Chen, C. Castillo, and R. Chellappa, “Crystal Loss and Quality Pooling for Unconstrained Face Verification and Recognition,” in arXiv.org, 2018.
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Pamela Shapiro and Kevin Duh, “BPE and CharCNNs for Translation of Morphology: A Cross-Lingual Comparison and Analysis,” in arXiv.org, 2018.
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Wei-An Lin, Jun-Cheng Chen, C. Castillo, and R. Chellappa, “Deep Density Clustering of Unconstrained Faces,” in 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018.
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Suwon Shon, N. Dehak, D. A. Reynolds, and James R. Glass, “MCE 2018: The 1st Multi-target Speaker Detection and Identification Challenge Evaluation (MCE) Plan, Dataset and Baseline System,” in arXiv.org, 2018.
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Ankan Bansal, Karan Sikka, Gaurav Sharma, R. Chellappa, and Ajay Divakaran, “Zero-Shot Object Detection,” in European Conference on Computer Vision, 2018.
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Y. Balaji, Martin Renqiang Min, Bing Bai, R. Chellappa, and H. Graf, “TFGAN: Improving Conditioning for Text-to-Video Synthesis.” 2018.
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Matthew Wiesner, Chunxi Liu, Lucas Ondel, Craig Harman, Vimal Manohar, J. Trmal, Zhongqiang Huang, S. Khudanpur, and N. Dehak, “The JHU Speech LOREHLT 2017 System: Cross-Language Transfer for Situation-Frame Detection,” in arXiv.org, 2018.
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M. Naphade, Ming-Ching Chang, Anuj Sharma, D. Anastasiu, Vamsi Jagarlamudi, Pranamesh Chakraborty, Tingting Huang, Shuo Wang, Ming-Yu Liu, R. Chellappa, Jenq-Neng Hwang, and Siwei Lyu, “The 2018 NVIDIA AI City Challenge,” in 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2018.
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P. Frederiksen, J. Villalba, Shinji Watanabe, Z. Tan, and N. Dehak, “Effectiveness of Single-Channel BLSTM Enhancement for Language Identification,” in Interspeech, 2018.
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Fred Richardson, P. Torres-Carrasquillo, Jonas Borgstrom, D. Sturim, Youngjune Gwon, J. Villalba, J. Trmal, Nanxin Chen, Réda Dehak, and N. Dehak, “The MIT Lincoln Laboratory / JHU / EPITA-LSE LRE17 System,” in The Speaker and Language Recognition Workshop, 2018.
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Emily M. Hand, C. Castillo, and R. Chellappa, “Predicting Facial Attributes in Video Using Temporal Coherence and Motion-Attention,” in IEEE Workshop/Winter Conference on Applications of Computer Vision, 2018.
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O. Scharenborg, Patrick Ebel, M. Hasegawa-Johnson, and N. Dehak, “Building an ASR System for Mboshi Using A Cross-Language Definition of Acoustic Units Approach,” in Workshop on Spoken Language Technologies for Under-resourced Languages, 2018.
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Ran Zhao, Yuntian Deng, Mark Dredze, Arun Verma, David S. Rosenberg, and Amanda Stent, “Visual Attention Model for Cross-sectional Stock Return Prediction and End-to-End Multimodal Market Representation Learning,” in The Florida AI Research Society, 2018.
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Li Liu, Jie Chen, P. Fieguth, Guoying Zhao, R. Chellappa, and M. Pietikäinen, “A Survey of Recent Advances in Texture Representation,” in arXiv.org, 2018.
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@inproceedings{49221985,
title = {Crosstalk between the immune system and neural pathways in interstitial cystitis/bladder pain syndrome.},
author = {{Kevin Duh} and {M. Funaro} and {W. DeGouveia} and {Sonia Bahlani} and {Dominic Pappas} and {S. Najjar} and {I. Tabansky} and {R. Moldwin} and {Joel N.H. Stern}},
year = 2018,
month = {5},
booktitle = {Discover medicine},
url = {https://www.semanticscholar.org/paper/02eea1717c357baa1eab58fc79d59860c0f5b002},
}

Pegah Ghahremani, P. S. Nidadavolu, Nanxin Chen, J. Villalba, Daniel Povey, S. Khudanpur, and N. Dehak, “End-to-end Deep Neural Network Age Estimation,” in Interspeech, 2018.
[BibTeX] [Link]

@inproceedings{52192343,
title = {End-to-end Deep Neural Network Age Estimation},
author = {{Pegah Ghahremani} and {P. S. Nidadavolu} and {Nanxin Chen} and {J. Villalba} and {Daniel Povey} and {S. Khudanpur} and {N. Dehak}},
year = 2018,
month = {9},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/c936edddcb803b9eb065b6128c6d0e28d5234db1},
}

H. Inaguma, X. Zhang, Z. Wang, A. Renduchintala, S. Watanabe, and K. Duh, “The JHU/KyotoU Speech Translation System for IWSLT 2018,” in Proceedings of the 15th International Conference on Spoken Language Translation, Brussels, 2018, p. 153–159.
[BibTeX] [Abstract] [Link]

This paper describes the Johns Hopkins University (JHU) and Kyoto University submissions to the Speech Translation evaluation campaign at IWSLT2018. Our end-to-end speech translation systems are based on ESPnet and implements an attention-based encoder-decoder model. As comparison, we also experiment with a pipeline system that uses independent neural network systems for both the speech transcription and text translation components. We find that a transfer learning approach that bootstraps the end-to-end speech translation system with speech transcription system{‘}s parameters is important for training on small datasets.

@inproceedings{inaguma-etal-2018-jhu,
title = "The {JHU}/{K}yoto{U} Speech Translation System for {IWSLT} 2018",
author = "Inaguma, Hirofumi and
Zhang, Xuan and
Wang, Zhiqi and
Renduchintala, Adithya and
Watanabe, Shinji and
Duh, Kevin",
editor = "Turchi, Marco and
Niehues, Jan and
Frederico, Marcello",
booktitle = "Proceedings of the 15th International Conference on Spoken Language Translation",
month = oct # " 29-30",
year = "2018",
address = "Brussels",
publisher = "International Conference on Spoken Language Translation",
url = "https://aclanthology.org/2018.iwslt-1.23",
pages = "153--159",
abstract = "This paper describes the Johns Hopkins University (JHU) and Kyoto University submissions to the Speech Translation evaluation campaign at IWSLT2018. Our end-to-end speech translation systems are based on ESPnet and implements an attention-based encoder-decoder model. As comparison, we also experiment with a pipeline system that uses independent neural network systems for both the speech transcription and text translation components. We find that a transfer learning approach that bootstraps the end-to-end speech translation system with speech transcription system{'}s parameters is important for training on small datasets.",
}

L. Moro-Velázquez, Jorge Andrés Gómez García, Juan Ignacio Godino-Llorente, J. Rusz, S. Skodda, F. Grandas, J. Velazquez, J. Orozco-Arroyave, Elmar Nöth, and N. Dehak, “Study of the Automatic Detection of Parkison’s Disease Based on Speaker Recognition Technologies and Allophonic Distillation,” in Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018.
[BibTeX] [Link]

@inproceedings{53093744,
title = {Study of the Automatic Detection of Parkison’s Disease Based on Speaker Recognition Technologies and Allophonic Distillation},
author = {{L. Moro-Velázquez} and {Jorge Andrés Gómez García} and {Juan Ignacio Godino-Llorente} and {J. Rusz} and {S. Skodda} and {F. Grandas} and {J. Velazquez} and {J. Orozco-Arroyave} and {Elmar Nöth} and {N. Dehak}},
year = 2018,
month = {7},
booktitle = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society},
url = {https://www.semanticscholar.org/paper/c2781fc03d99411ffdf102bc9a144a08d98474ba},
}

Enayat Ullah, Poorya Mianjy, T. V. Marinov, and R. Arora, “Streaming Kernel PCA with Õ(√n) Random Features,” in Neural Information Processing Systems, 2018.
[BibTeX] [Link]

@inproceedings{52110004,
title = {Streaming Kernel PCA with Õ(√n) Random Features},
author = {{Enayat Ullah} and {Poorya Mianjy} and {T. V. Marinov} and {R. Arora}},
year = 2018,
month = {8},
booktitle = {Neural Information Processing Systems},
url = {https://www.semanticscholar.org/paper/53f4f6f14ea5f426704d880de6ba3a35a62ebbd1},
}

Xiaodong Liu, Kevin Duh, and Jianfeng Gao, “Stochastic Answer Networks for Natural Language Inference,” in arXiv.org, 2018.
[BibTeX] [Link]

@inproceedings{5058361,
title = {Stochastic Answer Networks for Natural Language Inference},
author = {{Xiaodong Liu} and {Kevin Duh} and {Jianfeng Gao}},
year = 2018,
month = {4},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/6084b58d8b4b0caf3a2a7f3a1bee1cc527927e39},
}

A. Hammond, Michael J. Paul, J. Hobelmann, Animesh Koratana, Mark Dredze, and M. Chisolm, “Perceived Attitudes About Substance Use in Anonymous Social Media Posts Near College Campuses: Observational Study,” in JMIR Mental Health, 2018.
[BibTeX] [Link]

@inproceedings{51906494,
title = {Perceived Attitudes About Substance Use in Anonymous Social Media Posts Near College Campuses: Observational Study},
author = {{A. Hammond} and {Michael J. Paul} and {J. Hobelmann} and {Animesh Koratana} and {Mark Dredze} and {M. Chisolm}},
year = 2018,
month = {8},
booktitle = {JMIR Mental Health},
url = {https://www.semanticscholar.org/paper/47934ca0f914d869d8a756869949cf3ab95e1390},
}

Ankan Bansal, Rajeev Ranjan, C. Castillo, and R. Chellappa, “Deep Features for Recognizing Disguised Faces in the Wild,” in 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2018.
[BibTeX] [Link]

@inproceedings{53560998,
title = {Deep Features for Recognizing Disguised Faces in the Wild},
author = {{Ankan Bansal} and {Rajeev Ranjan} and {C. Castillo} and {R. Chellappa}},
year = 2018,
month = {6},
booktitle = {2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
url = {https://www.semanticscholar.org/paper/a50fa5048c61209149de0711b5f1b1806b43da00},
}

Tao Chen and Mark Dredze, “Vaccine Images on Twitter: Analysis of What Images are Shared,” in Journal of Medical Internet Research, 2018.
[BibTeX] [Link]

@inproceedings{4594103,
title = {Vaccine Images on Twitter: Analysis of What Images are Shared},
author = {{Tao Chen} and {Mark Dredze}},
year = 2018,
month = {4},
booktitle = {Journal of Medical Internet Research},
url = {https://www.semanticscholar.org/paper/0dfaf8504138e212d71eb0cc4940604eccfa7183},
}

Suhas Lohit, Ankan Bansal, Nitesh Shroff, Jaishanker K. Pillai, P. Turaga, and R. Chellappa, “Predicting Dynamical Evolution of Human Activities from a Single Image,” in 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2018.
[BibTeX] [Link]

@inproceedings{53417428,
title = {Predicting Dynamical Evolution of Human Activities from a Single Image},
author = {{Suhas Lohit} and {Ankan Bansal} and {Nitesh Shroff} and {Jaishanker K. Pillai} and {P. Turaga} and {R. Chellappa}},
year = 2018,
month = {6},
booktitle = {2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
url = {https://www.semanticscholar.org/paper/a53ccdab3bf4736fd6d6793436f028c52a8dc233},
}

Arthita Ghosh, Max Ehrlich, Sohil Shah, L. Davis, and R. Chellappa, “Stacked U-Nets for Ground Material Segmentation in Remote Sensing Imagery,” in 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2018.
[BibTeX] [Link]

@inproceedings{53646702,
title = {Stacked U-Nets for Ground Material Segmentation in Remote Sensing Imagery},
author = {{Arthita Ghosh} and {Max Ehrlich} and {Sohil Shah} and {L. Davis} and {R. Chellappa}},
year = 2018,
month = {6},
booktitle = {2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
url = {https://www.semanticscholar.org/paper/020ffb0a682ab6ddfad36e2f448a1e6e086083d7},
}

Navaneeth Bodla, G. Hua, and R. Chellappa, “Semi-supervised FusedGAN for Conditional Image Generation,” in European Conference on Computer Vision, 2018.
[BibTeX] [Link]

@inproceedings{7849608,
title = {Semi-supervised FusedGAN for Conditional Image Generation},
author = {{Navaneeth Bodla} and {G. Hua} and {R. Chellappa}},
year = 2018,
month = {1},
booktitle = {European Conference on Computer Vision},
url = {https://www.semanticscholar.org/paper/2727927c7493cef9785b3a06a38f5c1ce126fc23},
}

X. Lan, Shengping Zhang, P. Yuen, and R. Chellappa, “Learning Common and Feature-Specific Patterns: A Novel Multiple-Sparse-Representation-Based Tracker,” in IEEE Transactions on Image Processing, 2018.
[BibTeX] [Link]

@inproceedings{3295267,
title = {Learning Common and Feature-Specific Patterns: A Novel Multiple-Sparse-Representation-Based Tracker},
author = {{X. Lan} and {Shengping Zhang} and {P. Yuen} and {R. Chellappa}},
year = 2018,
month = {4},
booktitle = {IEEE Transactions on Image Processing},
url = {https://www.semanticscholar.org/paper/3c37c72458d01fc3b949aa4177631beaf3bf6696},
}

M. Naphade, Ming-Ching Chang, Anuj Sharma, D. Anastasiu, Vamsi Jagarlamudi, Pranamesh Chakraborty, Tingting Huang, Shuo Wang, Ming-Yu Liu, R. Chellappa, Jenq-Neng Hwang, and Siwei Lyu, “The NVIDIA AI City Challenge 2018.” 2018.
[BibTeX] [Link]

@inproceedings{53982224,
title = {The NVIDIA AI City Challenge 2018},
author = {{M. Naphade} and {Ming-Ching Chang} and {Anuj Sharma} and {D. Anastasiu} and {Vamsi Jagarlamudi} and {Pranamesh Chakraborty} and {Tingting Huang} and {Shuo Wang} and {Ming-Yu Liu} and {R. Chellappa} and {Jenq-Neng Hwang} and {Siwei Lyu}},
year = 2018,
booktitle = {},
url = {https://www.semanticscholar.org/paper/e23c0ab73b8a098d6e3e01200cade2d7603c70e3},
}

Li Liu, Jie Chen, P. Fieguth, Guoying Zhao, R. Chellappa, and M. Pietikäinen, “From BoW to CNN: Two Decades of Texture Representation for Texture Classification,” in International Journal of Computer Vision, 2018.
[BibTeX] [Link]

@inproceedings{52919290,
title = {From BoW to CNN: Two Decades of Texture Representation for Texture Classification},
author = {{Li Liu} and {Jie Chen} and {P. Fieguth} and {Guoying Zhao} and {R. Chellappa} and {M. Pietikäinen}},
year = 2018,
month = {1},
booktitle = {International Journal of Computer Vision},
url = {https://www.semanticscholar.org/paper/9175e4f461aaaddc87072e2b1451c8da7fdff7bb},
}

Travis Wolfe, Annabelle Carrell, Mark Dredze, and Benjamin Van Durme, “Summarizing Entities using Distantly Supervised Information Extractors,” in ProfS/KG4IR/Data:Search@SIGIR, 2018.
[BibTeX] [Link]

@inproceedings{49586717,
title = {Summarizing Entities using Distantly Supervised Information Extractors},
author = {{Travis Wolfe} and {Annabelle Carrell} and {Mark Dredze} and {Benjamin Van Durme}},
year = 2018,
booktitle = {ProfS/KG4IR/Data:Search@SIGIR},
url = {https://www.semanticscholar.org/paper/cab5f70ec2dfe9b33726217babc5ee6a42246a62},
}

Wei-An Lin, Jun-Cheng Chen, Rajeev Ranjan, Ankan Bansal, S. Sankaranarayanan, C. Castillo, and R. Chellappa, “Proximity-Aware Hierarchical Clustering of unconstrained faces,” in Image and Vision Computing, 2018.
[BibTeX] [Link]

@inproceedings{52883502,
title = {Proximity-Aware Hierarchical Clustering of unconstrained faces},
author = {{Wei-An Lin} and {Jun-Cheng Chen} and {Rajeev Ranjan} and {Ankan Bansal} and {S. Sankaranarayanan} and {C. Castillo} and {R. Chellappa}},
year = 2018,
month = {9},
booktitle = {Image and Vision Computing},
url = {https://www.semanticscholar.org/paper/bfe5e4d55af4b9aa7f7fe3dcc08cdd2a7bbfae6c},
}

Shuoyang Ding, Huda Khayrallah, Philipp Koehn, Matt Post, Manish Kumar, and Kevin Duh, “Machine Translation Systems for WMT 2017.” 2018.
[BibTeX] [Link]

@inproceedings{3897357,
title = {Machine Translation Systems for WMT 2017},
author = {{Shuoyang Ding} and {Huda Khayrallah} and {Philipp Koehn} and {Matt Post} and {Manish Kumar} and {Kevin Duh}},
year = 2018,
booktitle = {},
url = {https://www.semanticscholar.org/paper/9403fc63edbc94ef6598f227634c9e15b3a48551},
}

S. Zhang, X. Ma, R. Rudinger, K. Duh, and B. Van Durme, “Cross-lingual Decompositional Semantic Parsing,” in Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, 2018, p. 1664–1675. doi:10.18653/v1/D18-1194
[BibTeX] [Abstract] [Link]

We introduce the task of cross-lingual decompositional semantic parsing: mapping content provided in a source language into a decompositional semantic analysis based on a target language. We present: (1) a form of decompositional semantic analysis designed to allow systems to target varying levels of structural complexity (shallow to deep analysis), (2) an evaluation metric to measure the similarity between system output and reference semantic analysis, (3) an end-to-end model with a novel annotating mechanism that supports intra-sentential coreference, and (4) an evaluation dataset on which our model outperforms strong baselines by at least 1.75 F1 score.

@inproceedings{zhang-etal-2018-cross,
title = "Cross-lingual Decompositional Semantic Parsing",
author = "Zhang, Sheng and
Ma, Xutai and
Rudinger, Rachel and
Duh, Kevin and
Van Durme, Benjamin",
editor = "Riloff, Ellen and
Chiang, David and
Hockenmaier, Julia and
Tsujii, Jun{'}ichi",
booktitle = "Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing",
month = oct # "-" # nov,
year = "2018",
address = "Brussels, Belgium",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D18-1194",
doi = "10.18653/v1/D18-1194",
pages = "1664--1675",
abstract = "We introduce the task of cross-lingual decompositional semantic parsing: mapping content provided in a source language into a decompositional semantic analysis based on a target language. We present: (1) a form of decompositional semantic analysis designed to allow systems to target varying levels of structural complexity (shallow to deep analysis), (2) an evaluation metric to measure the similarity between system output and reference semantic analysis, (3) an end-to-end model with a novel annotating mechanism that supports intra-sentential coreference, and (4) an evaluation dataset on which our model outperforms strong baselines by at least 1.75 F1 score.",
}

Amit Kumar, Pirazh Khorramshahi, Wei-An Lin, Prithviraj Dhar, Jun-Cheng Chen, and R. Chellappa, “A Semi-Automatic 2D Solution for Vehicle Speed Estimation from Monocular Videos,” in 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2018.
[BibTeX] [Link]

@inproceedings{53512560,
title = {A Semi-Automatic 2D Solution for Vehicle Speed Estimation from Monocular Videos},
author = {{Amit Kumar} and {Pirazh Khorramshahi} and {Wei-An Lin} and {Prithviraj Dhar} and {Jun-Cheng Chen} and {R. Chellappa}},
year = 2018,
month = {6},
booktitle = {2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
url = {https://www.semanticscholar.org/paper/e45f68147a64fdadb64cf8103a486d5d0986f9e5},
}

Gregory Sell, David Snyder, A. McCree, D. Garcia-Romero, J. Villalba, Matthew Maciejewski, Vimal Manohar, N. Dehak, Daniel Povey, Shinji Watanabe, and S. Khudanpur, “Diarization is Hard: Some Experiences and Lessons Learned for the JHU Team in the Inaugural DIHARD Challenge,” in Interspeech, 2018.
[BibTeX] [Link]

@inproceedings{52187418,
title = {Diarization is Hard: Some Experiences and Lessons Learned for the JHU Team in the Inaugural DIHARD Challenge},
author = {{Gregory Sell} and {David Snyder} and {A. McCree} and {D. Garcia-Romero} and {J. Villalba} and {Matthew Maciejewski} and {Vimal Manohar} and {N. Dehak} and {Daniel Povey} and {Shinji Watanabe} and {S. Khudanpur}},
year = 2018,
month = {9},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/cf6352c789ab51320fa7ca9b1440c685b57fd769},
}

Matthew Maciejewski, David Snyder, Vimal Manohar, N. Dehak, and S. Khudanpur, “Characterizing Performance of Speaker Diarization Systems on Far-Field Speech Using Standard Methods,” in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2018.
[BibTeX] [Link]

@inproceedings{52291292,
title = {Characterizing Performance of Speaker Diarization Systems on Far-Field Speech Using Standard Methods},
author = {{Matthew Maciejewski} and {David Snyder} and {Vimal Manohar} and {N. Dehak} and {S. Khudanpur}},
year = 2018,
month = {4},
booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
url = {https://www.semanticscholar.org/paper/70217e8f8655923cfe1298c7b10be4fe2c1bab88},
}

P. Phillips, Amy N. Yates, Ying Hu, Carina A. Hahn, E. Noyes, Kelsey Jackson, J. G. Cavazos, G. Jeckeln, Rajeev Ranjan, S. Sankaranarayanan, Jun-Cheng Chen, C. Castillo, R. Chellappa, D. White, and A. O’toole, “Face recognition accuracy of forensic examiners, superrecognizers, and face recognition algorithms,” in Proceedings of the National Academy of Sciences of the United States of America, 2018.
[BibTeX] [Link]

@inproceedings{44171361,
title = {Face recognition accuracy of forensic examiners, superrecognizers, and face recognition algorithms},
author = {{P. Phillips} and {Amy N. Yates} and {Ying Hu} and {Carina A. Hahn} and {E. Noyes} and {Kelsey Jackson} and {J. G. Cavazos} and {G. Jeckeln} and {Rajeev Ranjan} and {S. Sankaranarayanan} and {Jun-Cheng Chen} and {C. Castillo} and {R. Chellappa} and {D. White} and {A. O’toole}},
year = 2018,
month = {5},
booktitle = {Proceedings of the National Academy of Sciences of the United States of America},
url = {https://www.semanticscholar.org/paper/8d9e4f3927dc32c685a01fe050707e4793b66e07},
}

Wei-An Lin, Jun-Cheng Chen, C. Castillo, and R. Chellappa, “Deep Density Clustering of Unconstrained Faces ( Supplementary Material ).” 2018.
[BibTeX] [Link]

@inproceedings{52846701,
title = {Deep Density Clustering of Unconstrained Faces ( Supplementary Material )},
author = {{Wei-An Lin} and {Jun-Cheng Chen} and {C. Castillo} and {R. Chellappa}},
year = 2018,
booktitle = {},
url = {https://www.semanticscholar.org/paper/23dd8d17ce09c22d367e4d62c1ccf507bcbc64da},
}

Jesús Antonio Villalba López, N. Brümmer, and N. Dehak, “End-to-End versus Embedding Neural Networks for Language Recognition in Mismatched Conditions,” in The Speaker and Language Recognition Workshop, 2018.
[BibTeX] [Link]

@inproceedings{51772236,
title = {End-to-End versus Embedding Neural Networks for Language Recognition in Mismatched Conditions},
author = {{Jesús Antonio Villalba López} and {N. Brümmer} and {N. Dehak}},
year = 2018,
month = {6},
booktitle = {The Speaker and Language Recognition Workshop},
url = {https://www.semanticscholar.org/paper/c92137e033c263bd4adde173438ccd2c90e8f170},
}

Amit Kumar and R. Chellappa, “Disentangling 3D Pose in a Dendritic CNN for Unconstrained 2D Face Alignment,” in 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018.
[BibTeX] [Link]

@inproceedings{3626281,
title = {Disentangling 3D Pose in a Dendritic CNN for Unconstrained 2D Face Alignment},
author = {{Amit Kumar} and {R. Chellappa}},
year = 2018,
month = {2},
booktitle = {2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition},
url = {https://www.semanticscholar.org/paper/8a85f0865930ea65239adb5ec2b97407c1446fa4},
}

Hongyu Xu, Xutao Lv, Xiaoyu Wang, Zhou Ren, and R. Chellappa, “Deep Regionlets for Object Detection,” in European Conference on Computer Vision, 2017.
[BibTeX] [Link]

@inproceedings{4393782,
title = {Deep Regionlets for Object Detection},
author = {{Hongyu Xu} and {Xutao Lv} and {Xiaoyu Wang} and {Zhou Ren} and {R. Chellappa}},
year = 2017,
month = {12},
booktitle = {European Conference on Computer Vision},
url = {https://www.semanticscholar.org/paper/f3d87142b80b7a10d33b6eb4d087ef5f2dd89cc9},
}

I. Doxas, A. Andreou, J. Lyon, V. Angelopoulos, San Lu, and P. Pritchett, “PerSEUS: Ultra-Low-Power High Performance Computing for Plasma Simulations.” 2017.
[BibTeX] [Link]

@inproceedings{217449336,
title = {PerSEUS: Ultra-Low-Power High Performance Computing for Plasma Simulations},
author = {{I. Doxas} and {A. Andreou} and {J. Lyon} and {V. Angelopoulos} and {San Lu} and {P. Pritchett}},
year = 2017,
month = {12},
booktitle = {},
url = {https://www.semanticscholar.org/paper/a6ca203e3c71f36055ac7b9680f3b2ffb2e12c63},
}

Ning Gao, Gregory Sell, Douglas W. Oard, and Mark Dredze, “Leveraging side information for speaker identification with the Enron conversational telephone speech collection,” in Automatic Speech Recognition & Understanding, 2017.
[BibTeX] [Link]

@inproceedings{3235059,
title = {Leveraging side information for speaker identification with the Enron conversational telephone speech collection},
author = {{Ning Gao} and {Gregory Sell} and {Douglas W. Oard} and {Mark Dredze}},
year = 2017,
month = {12},
booktitle = {Automatic Speech Recognition & Understanding},
url = {https://www.semanticscholar.org/paper/54016ad9d5b5a1155e7c22e4c9b947a2837ab7d5},
}

Rajeev Ranjan, S. Sankaranarayanan, C. Castillo, and R. Chellappa, “Improving Network Robustness against Adversarial Attacks with Compact Convolution,” in arXiv.org, 2017.
[BibTeX] [Link]

@inproceedings{4345097,
title = {Improving Network Robustness against Adversarial Attacks with Compact Convolution},
author = {{Rajeev Ranjan} and {S. Sankaranarayanan} and {C. Castillo} and {R. Chellappa}},
year = 2017,
month = {12},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/a0d809efbab73fa64bf2a82ab94f119f52870ea2},
}

H. Mei and J. Eisner, “The Neural Hawkes Process: A Neurally Self-Modulating Multivariate Point Process,” in Advances in Neural Information Processing Systems (NeurIPS), Long Beach, CA, 2017, p. 6754–6764.
[BibTeX] [Link]

@InProceedings{mei-eisner-2017,
author = "Hongyuan Mei and Jason Eisner",
title = "The Neural {H}awkes Process: {A} Neurally
Self-Modulating Multivariate Point Process",
booktitle = "Advances in Neural Information Processing Systems
(NeurIPS)",
year = "2017",
month = dec,
pages = "6754--6764",
address = "Long Beach, CA",
note = "First version December 2016 as
\href{https://arxiv.org/abs/1612.09328v1}{arXiv:1612.09328v1}.",
URL = "http://cs.jhu.edu/~jason/papers/#mei-eisner-2017",
}

H. Khayrallah, G. Kumar, K. Duh, M. Post, and P. Koehn, “Neural Lattice Search for Domain Adaptation in Machine Translation,” in Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers), Taipei, Taiwan, 2017, p. 20–25.
[BibTeX] [Abstract] [Link]

Domain adaptation is a major challenge for neural machine translation (NMT). Given unknown words or new domains, NMT systems tend to generate fluent translations at the expense of adequacy. We present a stack-based lattice search algorithm for NMT and show that constraining its search space with lattices generated by phrase-based machine translation (PBMT) improves robustness. We report consistent BLEU score gains across four diverse domain adaptation tasks involving medical, IT, Koran, or subtitles texts.

@inproceedings{khayrallah-etal-2017-neural,
title = "Neural Lattice Search for Domain Adaptation in Machine Translation",
author = "Khayrallah, Huda and
Kumar, Gaurav and
Duh, Kevin and
Post, Matt and
Koehn, Philipp",
editor = "Kondrak, Greg and
Watanabe, Taro",
booktitle = "Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)",
month = nov,
year = "2017",
address = "Taipei, Taiwan",
publisher = "Asian Federation of Natural Language Processing",
url = "https://aclanthology.org/I17-2004",
pages = "20--25",
abstract = "Domain adaptation is a major challenge for neural machine translation (NMT). Given unknown words or new domains, NMT systems tend to generate fluent translations at the expense of adequacy. We present a stack-based lattice search algorithm for NMT and show that constraining its search space with lattices generated by phrase-based machine translation (PBMT) improves robustness. We report consistent BLEU score gains across four diverse domain adaptation tasks involving medical, IT, Koran, or subtitles texts.",
}

A. S. White, P. Rastogi, K. Duh, and B. Van Durme, “Inference is Everything: Recasting Semantic Resources into a Unified Evaluation Framework,” in Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers), Taipei, Taiwan, 2017, p. 996–1005.
[BibTeX] [Abstract] [Link]

We propose to unify a variety of existing semantic classification tasks, such as semantic role labeling, anaphora resolution, and paraphrase detection, under the heading of Recognizing Textual Entailment (RTE). We present a general strategy to automatically generate one or more sentential hypotheses based on an input sentence and pre-existing manual semantic annotations. The resulting suite of datasets enables us to probe a statistical RTE model{‘}s performance on different aspects of semantics. We demonstrate the value of this approach by investigating the behavior of a popular neural network RTE model.

@inproceedings{white-etal-2017-inference,
title = "Inference is Everything: Recasting Semantic Resources into a Unified Evaluation Framework",
author = "White, Aaron Steven and
Rastogi, Pushpendre and
Duh, Kevin and
Van Durme, Benjamin",
editor = "Kondrak, Greg and
Watanabe, Taro",
booktitle = "Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)",
month = nov,
year = "2017",
address = "Taipei, Taiwan",
publisher = "Asian Federation of Natural Language Processing",
url = "https://aclanthology.org/I17-1100",
pages = "996--1005",
abstract = "We propose to unify a variety of existing semantic classification tasks, such as semantic role labeling, anaphora resolution, and paraphrase detection, under the heading of Recognizing Textual Entailment (RTE). We present a general strategy to automatically generate one or more sentential hypotheses based on an input sentence and pre-existing manual semantic annotations. The resulting suite of datasets enables us to probe a statistical RTE model{'}s performance on different aspects of semantics. We demonstrate the value of this approach by investigating the behavior of a popular neural network RTE model.",
}

R. Cotterell and K. Duh, “Low-Resource Named Entity Recognition with Cross-lingual, Character-Level Neural Conditional Random Fields,” in Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers), Taipei, Taiwan, 2017, p. 91–96.
[BibTeX] [Abstract] [Link]

Low-resource named entity recognition is still an open problem in NLP. Most state-of-the-art systems require tens of thousands of annotated sentences in order to obtain high performance. However, for most of the world{‘}s languages it is unfeasible to obtain such annotation. In this paper, we present a transfer learning scheme, whereby we train character-level neural CRFs to predict named entities for both high-resource languages and low-resource languages jointly. Learning character representations for multiple related languages allows knowledge transfer from the high-resource languages to the low-resource ones, improving F1 by up to 9.8 points.

@inproceedings{cotterell-duh-2017-low,
title = "Low-Resource Named Entity Recognition with Cross-lingual, Character-Level Neural Conditional Random Fields",
author = "Cotterell, Ryan and
Duh, Kevin",
editor = "Kondrak, Greg and
Watanabe, Taro",
booktitle = "Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)",
month = nov,
year = "2017",
address = "Taipei, Taiwan",
publisher = "Asian Federation of Natural Language Processing",
url = "https://aclanthology.org/I17-2016",
pages = "91--96",
abstract = "Low-resource named entity recognition is still an open problem in NLP. Most state-of-the-art systems require tens of thousands of annotated sentences in order to obtain high performance. However, for most of the world{'}s languages it is unfeasible to obtain such annotation. In this paper, we present a transfer learning scheme, whereby we train character-level neural CRFs to predict named entities for both high-resource languages and low-resource languages jointly. Learning character representations for multiple related languages allows knowledge transfer from the high-resource languages to the low-resource ones, improving F1 by up to 9.8 points.",
}

S. Noar, E. Leas, B. Althouse, Mark Dredze, Dannielle E Kelley, and J. Ayers, “Can a selfie promote public engagement with skin cancer?,” in Preventive Medicine, 2017.
[BibTeX] [Link]

@inproceedings{13954919,
title = {Can a selfie promote public engagement with skin cancer?},
author = {{S. Noar} and {E. Leas} and {B. Althouse} and {Mark Dredze} and {Dannielle E Kelley} and {J. Ayers}},
year = 2017,
month = {11},
booktitle = {Preventive Medicine},
url = {https://www.semanticscholar.org/paper/66630b0725f4a0924cef2f000a4ff3b017876769},
}

Jingjing Zheng, Zhuolin Jiang, and R. Chellappa, “Submodular Attribute Selection for Visual Recognition,” in IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017.
[BibTeX] [Link]

@inproceedings{24730594,
title = {Submodular Attribute Selection for Visual Recognition},
author = {{Jingjing Zheng} and {Zhuolin Jiang} and {R. Chellappa}},
year = 2017,
month = {11},
booktitle = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
url = {https://www.semanticscholar.org/paper/58eb9174211d58af76023ce33ee05769de57236c},
}

B. Van Durme, T. Lippincott, K. Duh, D. Burchfield, A. Poliak, C. Costello, T. Finin, S. Miller, J. Mayfield, P. Koehn, C. Harman, D. Lawrie, C. May, M. Thomas, A. Carrell, J. Chaloux, T. Chen, A. Comerford, M. Dredze, B. Glass, S. Hao, P. Martin, P. Rastogi, R. Sankepally, T. Wolfe, Y. Tran, and T. Zhang, “CADET: Computer Assisted Discovery Extraction and Translation,” in Proceedings of the IJCNLP 2017, System Demonstrations, Tapei, Taiwan, 2017, p. 5–8.
[BibTeX] [Abstract] [Link]

Computer Assisted Discovery Extraction and Translation (CADET) is a workbench for helping knowledge workers find, label, and translate documents of interest. It combines a multitude of analytics together with a flexible environment for customizing the workflow for different users. This open-source framework allows for easy development of new research prototypes using a micro-service architecture based atop Docker and Apache Thrift.

@inproceedings{van-durme-etal-2017-cadet,
title = "{CADET}: Computer Assisted Discovery Extraction and Translation",
author = "Van Durme, Benjamin and
Lippincott, Tom and
Duh, Kevin and
Burchfield, Deana and
Poliak, Adam and
Costello, Cash and
Finin, Tim and
Miller, Scott and
Mayfield, James and
Koehn, Philipp and
Harman, Craig and
Lawrie, Dawn and
May, Chandler and
Thomas, Max and
Carrell, Annabelle and
Chaloux, Julianne and
Chen, Tongfei and
Comerford, Alex and
Dredze, Mark and
Glass, Benjamin and
Hao, Shudong and
Martin, Patrick and
Rastogi, Pushpendre and
Sankepally, Rashmi and
Wolfe, Travis and
Tran, Ying-Ying and
Zhang, Ted",
editor = "Park, Seong-Bae and
Supnithi, Thepchai",
booktitle = "Proceedings of the {IJCNLP} 2017, System Demonstrations",
month = nov,
year = "2017",
address = "Tapei, Taiwan",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/I17-3002",
pages = "5--8",
abstract = "Computer Assisted Discovery Extraction and Translation (CADET) is a workbench for helping knowledge workers find, label, and translate documents of interest. It combines a multitude of analytics together with a flexible environment for customizing the workflow for different users. This open-source framework allows for easy development of new research prototypes using a micro-service architecture based atop Docker and Apache Thrift.",
}

S. Sankaranarayanan, Y. Balaji, Arpit Jain, Ser-Nam Lim, and R. Chellappa, “Unsupervised Domain Adaptation for Semantic Segmentation with GANs,” in arXiv.org, 2017.
[BibTeX] [Link]

@inproceedings{11247316,
title = {Unsupervised Domain Adaptation for Semantic Segmentation with GANs},
author = {{S. Sankaranarayanan} and {Y. Balaji} and {Arpit Jain} and {Ser-Nam Lim} and {R. Chellappa}},
year = 2017,
month = {11},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/ccd3dcbccae7d903608530bddf6381db8e723a7d},
}

F. Pereira, E. Silva, G. Lafruit, R. Chellappa, and S. Theodoridis, “Plenoptic Imaging: Representation and Processing.” 2017.
[BibTeX] [Link]

@inproceedings{63682836,
title = {Plenoptic Imaging: Representation and Processing},
author = {{F. Pereira} and {E. Silva} and {G. Lafruit} and {R. Chellappa} and {S. Theodoridis}},
year = 2017,
month = {11},
booktitle = {},
url = {https://www.semanticscholar.org/paper/dacfba59e24cb44605a7acb7372a3c5f565ad9dc},
}

D. Wang, N. Peng, and K. Duh, “A Multi-task Learning Approach to Adapting Bilingual Word Embeddings for Cross-lingual Named Entity Recognition,” in Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers), Taipei, Taiwan, 2017, p. 383–388.
[BibTeX] [Abstract] [Link]

We show how to adapt bilingual word embeddings (BWE{‘}s) to bootstrap a cross-lingual name-entity recognition (NER) system in a language with no labeled data. We assume a setting where we are given a comparable corpus with NER labels for the source language only; our goal is to build a NER model for the target language. The proposed multi-task model jointly trains bilingual word embeddings while optimizing a NER objective. This creates word embeddings that are both shared between languages and fine-tuned for the NER task.

@inproceedings{wang-etal-2017-multi,
title = "A Multi-task Learning Approach to Adapting Bilingual Word Embeddings for Cross-lingual Named Entity Recognition",
author = "Wang, Dingquan and
Peng, Nanyun and
Duh, Kevin",
editor = "Kondrak, Greg and
Watanabe, Taro",
booktitle = "Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)",
month = nov,
year = "2017",
address = "Taipei, Taiwan",
publisher = "Asian Federation of Natural Language Processing",
url = "https://aclanthology.org/I17-2065",
pages = "383--388",
abstract = "We show how to adapt bilingual word embeddings (BWE{'}s) to bootstrap a cross-lingual name-entity recognition (NER) system in a language with no labeled data. We assume a setting where we are given a comparable corpus with NER labels for the source language only; our goal is to build a NER model for the target language. The proposed multi-task model jointly trains bilingual word embeddings while optimizing a NER objective. This creates word embeddings that are both shared between languages and fine-tuned for the NER task.",
}

S. Zhang, K. Duh, and B. Van Durme, “Selective Decoding for Cross-lingual Open Information Extraction,” in Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers), Taipei, Taiwan, 2017, p. 832–842.
[BibTeX] [Abstract] [Link]

Cross-lingual open information extraction is the task of distilling facts from the source language into representations in the target language. We propose a novel encoder-decoder model for this problem. It employs a novel selective decoding mechanism, which explicitly models the sequence labeling process as well as the sequence generation process on the decoder side. Compared to a standard encoder-decoder model, selective decoding significantly increases the performance on a Chinese-English cross-lingual open IE dataset by 3.87-4.49 BLEU and 1.91-5.92 F1. We also extend our approach to low-resource scenarios, and gain promising improvement.

@inproceedings{zhang-etal-2017-selective,
title = "Selective Decoding for Cross-lingual Open Information Extraction",
author = "Zhang, Sheng and
Duh, Kevin and
Van Durme, Benjamin",
editor = "Kondrak, Greg and
Watanabe, Taro",
booktitle = "Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)",
month = nov,
year = "2017",
address = "Taipei, Taiwan",
publisher = "Asian Federation of Natural Language Processing",
url = "https://aclanthology.org/I17-1084",
pages = "832--842",
abstract = "Cross-lingual open information extraction is the task of distilling facts from the source language into representations in the target language. We propose a novel encoder-decoder model for this problem. It employs a novel selective decoding mechanism, which explicitly models the sequence labeling process as well as the sequence generation process on the decoder side. Compared to a standard encoder-decoder model, selective decoding significantly increases the performance on a Chinese-English cross-lingual open IE dataset by 3.87-4.49 BLEU and 1.91-5.92 F1. We also extend our approach to low-resource scenarios, and gain promising improvement.",
}

S. Sankaranarayanan, Y. Balaji, Arpit Jain, Ser-Nam Lim, and R. Chellappa, “Learning from Synthetic Data: Addressing Domain Shift for Semantic Segmentation,” in 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2017.
[BibTeX] [Link]

@inproceedings{4540721,
title = {Learning from Synthetic Data: Addressing Domain Shift for Semantic Segmentation},
author = {{S. Sankaranarayanan} and {Y. Balaji} and {Arpit Jain} and {Ser-Nam Lim} and {R. Chellappa}},
year = 2017,
month = {11},
booktitle = {2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition},
url = {https://www.semanticscholar.org/paper/dfd72b994765a1979c6872fc8948657885a31752},
}

Chris Paxton, Kapil D. Katyal, C. Rupprecht, R. Arora, and Gregory Hager, “Learning to Imagine Manipulation Goals for Robot Task Planning,” in arXiv.org, 2017.
[BibTeX] [Link]

@inproceedings{25044213,
title = {Learning to Imagine Manipulation Goals for Robot Task Planning},
author = {{Chris Paxton} and {Kapil D. Katyal} and {C. Rupprecht} and {R. Arora} and {Gregory Hager}},
year = 2017,
month = {11},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/778f8258bad0620b996666d883ce261216558ddd},
}

Y. Shen, X. Liu, K. Duh, and J. Gao, “An Empirical Analysis of Multiple-Turn Reasoning Strategies in Reading Comprehension Tasks,” in Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers), Taipei, Taiwan, 2017, p. 957–966.
[BibTeX] [Abstract] [Link]

Reading comprehension (RC) is a challenging task that requires synthesis of information across sentences and multiple turns of reasoning. Using a state-of-the-art RC model, we empirically investigate the performance of single-turn and multiple-turn reasoning on the SQuAD and MS MARCO datasets. The RC model is an end-to-end neural network with iterative attention, and uses reinforcement learning to dynamically control the number of turns. We find that multiple-turn reasoning outperforms single-turn reasoning for all question and answer types; further, we observe that enabling a flexible number of turns generally improves upon a fixed multiple-turn strategy. {\%}across all question types, and is particularly beneficial to questions with lengthy, descriptive answers. We achieve results competitive to the state-of-the-art on these two datasets.

@inproceedings{shen-etal-2017-empirical,
title = "An Empirical Analysis of Multiple-Turn Reasoning Strategies in Reading Comprehension Tasks",
author = "Shen, Yelong and
Liu, Xiaodong and
Duh, Kevin and
Gao, Jianfeng",
editor = "Kondrak, Greg and
Watanabe, Taro",
booktitle = "Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)",
month = nov,
year = "2017",
address = "Taipei, Taiwan",
publisher = "Asian Federation of Natural Language Processing",
url = "https://aclanthology.org/I17-1096",
pages = "957--966",
abstract = "Reading comprehension (RC) is a challenging task that requires synthesis of information across sentences and multiple turns of reasoning. Using a state-of-the-art RC model, we empirically investigate the performance of single-turn and multiple-turn reasoning on the SQuAD and MS MARCO datasets. The RC model is an end-to-end neural network with iterative attention, and uses reinforcement learning to dynamically control the number of turns. We find that multiple-turn reasoning outperforms single-turn reasoning for all question and answer types; further, we observe that enabling a flexible number of turns generally improves upon a fixed multiple-turn strategy. {\%}across all question types, and is particularly beneficial to questions with lengthy, descriptive answers. We achieve results competitive to the state-of-the-art on these two datasets.",
}

Theodore L. Caputi, E. Leas, Mark Dredze, Joanna E. Cohen, and J. Ayers, “They’re heating up: Internet search query trends reveal significant public interest in heat-not-burn tobacco products,” in PLoS ONE, 2017.
[BibTeX] [Link]

@inproceedings{25120614,
title = {They’re heating up: Internet search query trends reveal significant public interest in heat-not-burn tobacco products},
author = {{Theodore L. Caputi} and {E. Leas} and {Mark Dredze} and {Joanna E. Cohen} and {J. Ayers}},
year = 2017,
month = {10},
booktitle = {PLoS ONE},
url = {https://www.semanticscholar.org/paper/58ee4d7d99d2c34585324cc5e01a9eaf6fd8b448},
}

G. Stein-O’Brien, R. Arora, A. Culhane, Alexander V. Favorov, C. Greene, L. Goff, Yifeng Li, Aloune Ngom, M. Ochs, Yanun Xu, and E. Fertig, “Enter the matrix: Interpreting unsupervised feature learning with matrix decomposition to discover hidden knowledge in high-throughput omics data,” in bioRxiv, 2017.
[BibTeX] [Link]

@inproceedings{91732240,
title = {Enter the matrix: Interpreting unsupervised feature learning with matrix decomposition to discover hidden knowledge in high-throughput omics data},
author = {{G. Stein-O’Brien} and {R. Arora} and {A. Culhane} and {Alexander V. Favorov} and {C. Greene} and {L. Goff} and {Yifeng Li} and {Aloune Ngom} and {M. Ochs} and {Yanun Xu} and {E. Fertig}},
year = 2017,
month = {10},
booktitle = {bioRxiv},
url = {https://www.semanticscholar.org/paper/1db74eb4555795457185fb75a5b70d17e2047257},
}

Ning Gao, Mark Dredze, and Douglas W. Oard, “Person entity linking in email with NIL detection,” in J. Assoc. Inf. Sci. Technol., 2017.
[BibTeX] [Link]

@inproceedings{29303853,
title = {Person entity linking in email with NIL detection},
author = {{Ning Gao} and {Mark Dredze} and {Douglas W. Oard}},
year = 2017,
month = {10},
booktitle = {J. Assoc. Inf. Sci. Technol.},
url = {https://www.semanticscholar.org/paper/c7660f51186490edba345ca6dc7c987435484a9e},
}

J. Ayers, B. Althouse, E. Leas, Mark Dredze, and Jon-Patrick Allem, “Internet Searches for Suicide Following the Release of 13 Reasons Why,” in JAMA Internal Medicine, 2017.
[BibTeX] [Link]

@inproceedings{3547546,
title = {Internet Searches for Suicide Following the Release of 13 Reasons Why},
author = {{J. Ayers} and {B. Althouse} and {E. Leas} and {Mark Dredze} and {Jon-Patrick Allem}},
year = 2017,
month = {10},
booktitle = {JAMA Internal Medicine},
url = {https://www.semanticscholar.org/paper/4691e85460b30358590c0fa109c543512c27499f},
}

S. Ding, H. Khayrallah, P. Koehn, M. Post, G. Kumar, and K. Duh, “The JHU Machine Translation Systems for WMT 2017,” in Proceedings of the Second Conference on Machine Translation, Copenhagen, Denmark, 2017, p. 276–282. doi:10.18653/v1/W17-4724
[BibTeX] [Link]

@inproceedings{ding-etal-2017-jhu,
title = "The {JHU} Machine Translation Systems for {WMT} 2017",
author = "Ding, Shuoyang and
Khayrallah, Huda and
Koehn, Philipp and
Post, Matt and
Kumar, Gaurav and
Duh, Kevin",
editor = "Bojar, Ond{\v{r}}ej and
Buck, Christian and
Chatterjee, Rajen and
Federmann, Christian and
Graham, Yvette and
Haddow, Barry and
Huck, Matthias and
Yepes, Antonio Jimeno and
Koehn, Philipp and
Kreutzer, Julia",
booktitle = "Proceedings of the Second Conference on Machine Translation",
month = sep,
year = "2017",
address = "Copenhagen, Denmark",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W17-4724",
doi = "10.18653/v1/W17-4724",
pages = "276--282",
}

A. Andy, M. Dredze, M. Rwebangira, and C. Callison-Burch, “Constructing an Alias List for Named Entities during an Event,” in Proceedings of the 3rd Workshop on Noisy User-generated Text, Copenhagen, Denmark, 2017, p. 40–44. doi:10.18653/v1/W17-4405
[BibTeX] [Abstract] [Link]

In certain fields, real-time knowledge from events can help in making informed decisions. In order to extract pertinent real-time knowledge related to an event, it is important to identify the named entities and their corresponding aliases related to the event. The problem of identifying aliases of named entities that spike has remained unexplored. In this paper, we introduce an algorithm, EntitySpike, that identifies entities that spike in popularity in tweets from a given time period, and constructs an alias list for these spiked entities. EntitySpike uses a temporal heuristic to identify named entities with similar context that occur in the same time period (within minutes) during an event. Each entity is encoded as a vector using this temporal heuristic. We show how these entity-vectors can be used to create a named entity alias list. We evaluated our algorithm on a dataset of temporally ordered tweets from a single event, the 2013 Grammy Awards show. We carried out various experiments on tweets that were published in the same time period and show that our algorithm identifies most entity name aliases and outperforms a competitive baseline.

@inproceedings{andy-etal-2017-constructing,
title = "Constructing an Alias List for Named Entities during an Event",
author = "Andy, Anietie and
Dredze, Mark and
Rwebangira, Mugizi and
Callison-Burch, Chris",
editor = "Derczynski, Leon and
Xu, Wei and
Ritter, Alan and
Baldwin, Tim",
booktitle = "Proceedings of the 3rd Workshop on Noisy User-generated Text",
month = sep,
year = "2017",
address = "Copenhagen, Denmark",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W17-4405",
doi = "10.18653/v1/W17-4405",
pages = "40--44",
abstract = "In certain fields, real-time knowledge from events can help in making informed decisions. In order to extract pertinent real-time knowledge related to an event, it is important to identify the named entities and their corresponding aliases related to the event. The problem of identifying aliases of named entities that spike has remained unexplored. In this paper, we introduce an algorithm, EntitySpike, that identifies entities that spike in popularity in tweets from a given time period, and constructs an alias list for these spiked entities. EntitySpike uses a temporal heuristic to identify named entities with similar context that occur in the same time period (within minutes) during an event. Each entity is encoded as a vector using this temporal heuristic. We show how these entity-vectors can be used to create a named entity alias list. We evaluated our algorithm on a dataset of temporally ordered tweets from a single event, the 2013 Grammy Awards show. We carried out various experiments on tweets that were published in the same time period and show that our algorithm identifies most entity name aliases and outperforms a competitive baseline.",
}

Z. Wood-Doughty, M. Smith, D. Broniatowski, and M. Dredze, “How Does Twitter User Behavior Vary Across Demographic Groups?,” in Proceedings of the Second Workshop on NLP and Computational Social Science, Vancouver, Canada, 2017, p. 83–89. doi:10.18653/v1/W17-2912
[BibTeX] [Abstract] [Link]

Demographically-tagged social media messages are a common source of data for computational social science. While these messages can indicate differences in beliefs and behaviors between demographic groups, we do not have a clear understanding of how different demographic groups use platforms such as Twitter. This paper presents a preliminary analysis of how groups{‘} differing behaviors may confound analyses of the groups themselves. We analyzed one million Twitter users by first inferring demographic attributes, and then measuring several indicators of Twitter behavior. We find differences in these indicators across demographic groups, suggesting that there may be underlying differences in how different demographic groups use Twitter.

@inproceedings{wood-doughty-etal-2017-twitter,
title = "How Does {T}witter User Behavior Vary Across Demographic Groups?",
author = "Wood-Doughty, Zach and
Smith, Michael and
Broniatowski, David and
Dredze, Mark",
editor = {Hovy, Dirk and
Volkova, Svitlana and
Bamman, David and
Jurgens, David and
O{'}Connor, Brendan and
Tsur, Oren and
Do{\u{g}}ru{\"o}z, A. Seza},
booktitle = "Proceedings of the Second Workshop on {NLP} and Computational Social Science",
month = aug,
year = "2017",
address = "Vancouver, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W17-2912",
doi = "10.18653/v1/W17-2912",
pages = "83--89",
abstract = "Demographically-tagged social media messages are a common source of data for computational social science. While these messages can indicate differences in beliefs and behaviors between demographic groups, we do not have a clear understanding of how different demographic groups use platforms such as Twitter. This paper presents a preliminary analysis of how groups{'} differing behaviors may confound analyses of the groups themselves. We analyzed one million Twitter users by first inferring demographic attributes, and then measuring several indicators of Twitter behavior. We find differences in these indicators across demographic groups, suggesting that there may be underlying differences in how different demographic groups use Twitter.",
}

N. Peng and M. Dredze, “Multi-task Domain Adaptation for Sequence Tagging,” in Proceedings of the 2nd Workshop on Representation Learning for NLP, Vancouver, Canada, 2017, p. 91–100. doi:10.18653/v1/W17-2612
[BibTeX] [Abstract] [Link]

Many domain adaptation approaches rely on learning cross domain shared representations to transfer the knowledge learned in one domain to other domains. Traditional domain adaptation only considers adapting for one task. In this paper, we explore multi-task representation learning under the domain adaptation scenario. We propose a neural network framework that supports domain adaptation for multiple tasks simultaneously, and learns shared representations that better generalize for domain adaptation. We apply the proposed framework to domain adaptation for sequence tagging problems considering two tasks: Chinese word segmentation and named entity recognition. Experiments show that multi-task domain adaptation works better than disjoint domain adaptation for each task, and achieves the state-of-the-art results for both tasks in the social media domain.

@inproceedings{peng-dredze-2017-multi,
title = "Multi-task Domain Adaptation for Sequence Tagging",
author = "Peng, Nanyun and
Dredze, Mark",
editor = "Blunsom, Phil and
Bordes, Antoine and
Cho, Kyunghyun and
Cohen, Shay and
Dyer, Chris and
Grefenstette, Edward and
Hermann, Karl Moritz and
Rimell, Laura and
Weston, Jason and
Yih, Scott",
booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
month = aug,
year = "2017",
address = "Vancouver, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W17-2612",
doi = "10.18653/v1/W17-2612",
pages = "91--100",
abstract = "Many domain adaptation approaches rely on learning cross domain shared representations to transfer the knowledge learned in one domain to other domains. Traditional domain adaptation only considers adapting for one task. In this paper, we explore multi-task representation learning under the domain adaptation scenario. We propose a neural network framework that supports domain adaptation for multiple tasks simultaneously, and learns shared representations that better generalize for domain adaptation. We apply the proposed framework to domain adaptation for sequence tagging problems considering two tasks: Chinese word segmentation and named entity recognition. Experiments show that multi-task domain adaptation works better than disjoint domain adaptation for each task, and achieves the state-of-the-art results for both tasks in the social media domain.",
}

R. Cotterell, C. Kirov, John Sylak-Glassman, G. Walther, Ekaterina Vylomova, P. Xia, M. Faruqui, Sandra Kübler, D. Yarowsky, J. Eisner, and M. Hulden, “CoNLL-SIGMORPHON 2017 Shared Task: Universal Morphological Reinflection in 52 Languages,” in Proceedings of the Conference on Natural Language Learning: CoNLL-SIGMORPHON Shared Task System Descriptions, Vancouver, 2017, p. 1–30. doi:10.18653/v1/K17-2001
[BibTeX] [Link]

@InProceedings{cotterell-et-al-2017-shared,
aclid = "K17-2001",
doi = "10.18653/v1/K17-2001",
author = "Ryan Cotterell and Christo Kirov and John
Sylak-Glassman and G\'{e}raldine Walther and Ekaterina
Vylomova and Patrick Xia and Manaal Faruqui and Sandra
K{\"{u}}bler and David Yarowsky and Jason Eisner and
Mans Hulden",
title = "{CoNLL}-{SIGMORPHON} 2017 Shared Task: Universal
Morphological Reinflection in 52 Languages",
booktitle = "Proceedings of the Conference on Natural Language
Learning: CoNLL-SIGMORPHON Shared Task System
Descriptions",
pages = "1--30",
year = "2017",
month = aug,
address = "Vancouver",
URL = "http://cs.jhu.edu/~jason/papers/#cotterell-et-al-2017-shared",
}

A. Renduchintala, P. Koehn, and Jason Eisner, “Knowledge Tracing in Sequential Learning of Inflected Vocabulary,” in Proceedings of the Conference on Natural Language Learning (CoNLL), Vancouver, 2017, p. 238–247. doi:10.18653/v1/K17-1025
[BibTeX] [Link]

@InProceedings{renduchintala-et-al-2017-conll,
aclid = "K17-1025",
doi = "10.18653/v1/K17-1025",
author = "Adithya Renduchintala and Philipp Koehn and Jason
Eisner",
title = "Knowledge Tracing in Sequential Learning of Inflected
Vocabulary",
booktitle = "Proceedings of the Conference on Natural Language
Learning (CoNLL)",
pages = "238--247",
year = "2017",
month = aug,
address = "Vancouver",
URL = "http://cs.jhu.edu/~jason/papers/#renduchintala-et-al-2017-conll",
}

R. Cotterell and J. Eisner, “Probabilistic Typology: Deep Generative Models of Vowel Inventories,” in Proceedings of the Association for Computational Linguistics (ACL), Vancouver, 2017, p. 1182–1192. doi:10.18653/v1/P17-1109
[BibTeX] [Link]

@InProceedings{cotterell-eisner-2017-acl,
aclid = "P17-1109",
doi = "10.18653/v1/P17-1109",
author = "Ryan Cotterell and Jason Eisner",
title = "Probabilistic Typology: Deep Generative Models of
Vowel Inventories",
booktitle = "Proceedings of the Association for Computational
Linguistics (ACL)",
pages = "1182--1192",
year = "2017",
month = aug,
address = "Vancouver",
note = "Best Long Paper Award.",
URL = "http://cs.jhu.edu/~jason/papers/#cotterell-eisner-2017-acl",
}

N. Andrews, M. Dredze, B. Van Durme, and J. Eisner, “Bayesian Modeling of Lexical Resources for Low-Resource Settings,” in Proceedings of the Association for Computational Linguistics (ACL), Vancouver, 2017, p. 1029–1039. doi:10.18653/v1/P17-1095
[BibTeX] [Link]

@InProceedings{andrews-et-al-2017,
aclid = "P17-1095",
doi = "10.18653/v1/P17-1095",
author = "Nicholas Andrews and Mark Dredze and Benjamin Van
Durme and Jason Eisner",
title = "Bayesian Modeling of Lexical Resources for
Low-Resource Settings",
booktitle = "Proceedings of the Association for Computational
Linguistics (ACL)",
pages = "1029--1039",
year = "2017",
month = aug,
address = "Vancouver",
URL = "http://cs.jhu.edu/~jason/papers/#andrews-et-al-2017",
}

T. Wolfe, M. Dredze, and B. Van Durme, “Pocket Knowledge Base Population,” in Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), Vancouver, Canada, 2017, p. 305–310. doi:10.18653/v1/P17-2048
[BibTeX] [Abstract] [Link]

Existing Knowledge Base Population methods extract relations from a closed relational schema with limited coverage leading to sparse KBs. We propose Pocket Knowledge Base Population (PKBP), the task of dynamically constructing a KB of entities related to a query and finding the best characterization of relationships between entities. We describe novel Open Information Extraction methods which leverage the PKB to find informative trigger words. We evaluate using existing KBP shared-task data as well anew annotations collected for this work. Our methods produce high quality KB from just text with many more entities and relationships than existing KBP systems.

@inproceedings{wolfe-etal-2017-pocket,
title = "Pocket Knowledge Base Population",
author = "Wolfe, Travis and
Dredze, Mark and
Van Durme, Benjamin",
editor = "Barzilay, Regina and
Kan, Min-Yen",
booktitle = "Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)",
month = jul,
year = "2017",
address = "Vancouver, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P17-2048",
doi = "10.18653/v1/P17-2048",
pages = "305--310",
abstract = "Existing Knowledge Base Population methods extract relations from a closed relational schema with limited coverage leading to sparse KBs. We propose Pocket Knowledge Base Population (PKBP), the task of dynamically constructing a KB of entities related to a query and finding the best characterization of relationships between entities. We describe novel Open Information Extraction methods which leverage the PKB to find informative trigger words. We evaluate using existing KBP shared-task data as well anew annotations collected for this work. Our methods produce high quality KB from just text with many more entities and relationships than existing KBP systems.",
}

N. Andrews, M. Dredze, B. Van Durme, and J. Eisner, “Bayesian Modeling of Lexical Resources for Low-Resource Settings,” in Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Vancouver, Canada, 2017, p. 1029–1039. doi:10.18653/v1/P17-1095
[BibTeX] [Abstract] [Link]

Lexical resources such as dictionaries and gazetteers are often used as auxiliary data for tasks such as part-of-speech induction and named-entity recognition. However, discriminative training with lexical features requires annotated data to reliably estimate the lexical feature weights and may result in overfitting the lexical features at the expense of features which generalize better. In this paper, we investigate a more robust approach: we stipulate that the lexicon is the result of an assumed generative process. Practically, this means that we may treat the lexical resources as observations under the proposed generative model. The lexical resources provide training data for the generative model without requiring separate data to estimate lexical feature weights. We evaluate the proposed approach in two settings: part-of-speech induction and low-resource named-entity recognition.

@inproceedings{andrews-etal-2017-bayesian,
title = "{B}ayesian Modeling of Lexical Resources for Low-Resource Settings",
author = "Andrews, Nicholas and
Dredze, Mark and
Van Durme, Benjamin and
Eisner, Jason",
editor = "Barzilay, Regina and
Kan, Min-Yen",
booktitle = "Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = jul,
year = "2017",
address = "Vancouver, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P17-1095",
doi = "10.18653/v1/P17-1095",
pages = "1029--1039",
abstract = "Lexical resources such as dictionaries and gazetteers are often used as auxiliary data for tasks such as part-of-speech induction and named-entity recognition. However, discriminative training with lexical features requires annotated data to reliably estimate the lexical feature weights and may result in overfitting the lexical features at the expense of features which generalize better. In this paper, we investigate a more robust approach: we stipulate that the lexicon is the result of an assumed generative process. Practically, this means that we may treat the lexical resources as observations under the proposed generative model. The lexical resources provide training data for the generative model without requiring separate data to estimate lexical feature weights. We evaluate the proposed approach in two settings: part-of-speech induction and low-resource named-entity recognition.",
}

T. Vieira, M. Francis-Landau, N. Filardo, F. Khorasani, and J. Eisner, “Dyna: Toward a Self-Optimizing Declarative Language for Machine Learning Applications,” in Proceedings of the First ACM SIGPLAN Workshop on Machine Learning and Programming Languages (MAPL), Barcelona, 2017, p. 8–17. doi:10.1145/3088525.3088562
[BibTeX] [Link]

@InProceedings{vieira-et-al-2017,
doi = "10.1145/3088525.3088562",
author = "Tim Vieira and Matthew Francis-Landau and Nathaniel
Wesley Filardo and Farzad Khorasani and Jason Eisner",
title = "Dyna: Toward a Self-Optimizing Declarative Language
for Machine Learning Applications",
booktitle = "Proceedings of the First ACM SIGPLAN Workshop on
Machine Learning and Programming Languages (MAPL)",
pages = "8--17",
year = "2017",
month = jun,
address = "Barcelona",
publisher = "ACM",
ISBN = "978-1-4503-5071-6",
URL = "http://cs.jhu.edu/~jason/papers/#vieira-et-al-2017",
}

A. Benton, G. Coppersmith, and M. Dredze, “Ethical Research Protocols for Social Media Health Research,” in Proceedings of the First ACL Workshop on Ethics in Natural Language Processing, Valencia, Spain, 2017, p. 94–102. doi:10.18653/v1/W17-1612
[BibTeX] [Abstract] [Link]

Social media have transformed data-driven research in political science, the social sciences, health, and medicine. Since health research often touches on sensitive topics that relate to ethics of treatment and patient privacy, similar ethical considerations should be acknowledged when using social media data in health research. While much has been said regarding the ethical considerations of social media research, health research leads to an additional set of concerns. We provide practical suggestions in the form of guidelines for researchers working with social media data in health research. These guidelines can inform an IRB proposal for researchers new to social media health research.

@inproceedings{benton-etal-2017-ethical,
title = "Ethical Research Protocols for Social Media Health Research",
author = "Benton, Adrian and
Coppersmith, Glen and
Dredze, Mark",
editor = "Hovy, Dirk and
Spruit, Shannon and
Mitchell, Margaret and
Bender, Emily M. and
Strube, Michael and
Wallach, Hanna",
booktitle = "Proceedings of the First {ACL} Workshop on Ethics in Natural Language Processing",
month = apr,
year = "2017",
address = "Valencia, Spain",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W17-1612",
doi = "10.18653/v1/W17-1612",
pages = "94--102",
abstract = "Social media have transformed data-driven research in political science, the social sciences, health, and medicine. Since health research often touches on sensitive topics that relate to ethics of treatment and patient privacy, similar ethical considerations should be acknowledged when using social media data in health research. While much has been said regarding the ethical considerations of social media research, health research leads to an additional set of concerns. We provide practical suggestions in the form of guidelines for researchers working with social media data in health research. These guidelines can inform an IRB proposal for researchers new to social media health research.",
}

S. Zhang, K. Duh, and B. Van Durme, “MT/IE: Cross-lingual Open Information Extraction with Neural Sequence-to-Sequence Models,” in Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, Valencia, Spain, 2017, p. 64–70.
[BibTeX] [Abstract] [Link]

Cross-lingual information extraction is the task of distilling facts from foreign language (e.g. Chinese text) into representations in another language that is preferred by the user (e.g. English tuples). Conventional pipeline solutions decompose the task as machine translation followed by information extraction (or vice versa). We propose a joint solution with a neural sequence model, and show that it outperforms the pipeline in a cross-lingual open information extraction setting by 1-4 BLEU and 0.5-0.8 F1.

@inproceedings{zhang-etal-2017-mt,
title = "{MT}/{IE}: Cross-lingual Open Information Extraction with Neural Sequence-to-Sequence Models",
author = "Zhang, Sheng and
Duh, Kevin and
Van Durme, Benjamin",
editor = "Lapata, Mirella and
Blunsom, Phil and
Koller, Alexander",
booktitle = "Proceedings of the 15th Conference of the {E}uropean Chapter of the Association for Computational Linguistics: Volume 2, Short Papers",
month = apr,
year = "2017",
address = "Valencia, Spain",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/E17-2011",
pages = "64--70",
abstract = "Cross-lingual information extraction is the task of distilling facts from foreign language (e.g. Chinese text) into representations in another language that is preferred by the user (e.g. English tuples). Conventional pipeline solutions decompose the task as machine translation followed by information extraction (or vice versa). We propose a joint solution with a neural sequence model, and show that it outperforms the pipeline in a cross-lingual open information extraction setting by 1-4 BLEU and 0.5-0.8 F1.",
}

R. Cotterell, A. Poliak, B. V. Durme, and J. Eisner, “Explaining and Generalizing Skip-Gram through Exponential Family Principal Component Analysis,” in Proceedings of the Conference of the European Chapter of the Association for Computational Linguistics: Human Language Technologies (EACL), Valencia, Spain, 2017, p. 175–181. doi:10.18653/v1/E17-2028
[BibTeX] [Link]

@InProceedings{cotterell-et-al-2017-eacl,
aclid = "E17-2028",
doi = "10.18653/v1/E17-2028",
author = "Ryan Cotterell and Adam Poliak and Benjamin Van Durme
and Jason Eisner",
title = "Explaining and Generalizing Skip-Gram through
Exponential Family Principal Component Analysis",
booktitle = "Proceedings of the Conference of the European Chapter
of the Association for Computational Linguistics: Human
Language Technologies (EACL)",
pages = "175--181",
year = "2017",
month = apr,
address = "Valencia, Spain",
URL = "http://cs.jhu.edu/~jason/papers/#cotterell-et-al-2017-eacl",
}

Fei Cheng, Kevin Duh, and Yuji Matsumoto, “Towards a Consistent Segmentation Level across Multiple Chinese Word Segmentation Corpora.” 2017.
[BibTeX] [Link]

@inproceedings{59332257,
title = {Towards a Consistent Segmentation Level across Multiple Chinese Word Segmentation Corpora},
author = {{Fei Cheng} and {Kevin Duh} and {Yuji Matsumoto}},
year = 2017,
booktitle = {},
url = {https://www.semanticscholar.org/paper/b8cebc298ab89f46274ce42ef7e9d6acfd19e345},
}

Pouya Samangouei, Emily M. Hand, Vishal M. Patel, and R. Chellappa, “Active authentication using facial attributes.” 2017.
[BibTeX] [Link]

@inproceedings{196152770,
title = {Active authentication using facial attributes},
author = {{Pouya Samangouei} and {Emily M. Hand} and {Vishal M. Patel} and {R. Chellappa}},
year = 2017,
month = {9},
booktitle = {},
url = {https://www.semanticscholar.org/paper/7a3764a4ea3026de50ec0a4c3e00f0cae0bffc0c},
}

S. Sankaranarayanan, Y. Balaji, C. Castillo, and R. Chellappa, “Generate to Adapt: Aligning Domains Using Generative Adversarial Networks,” in 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2017.
[BibTeX] [Link]

@inproceedings{4547917,
title = {Generate to Adapt: Aligning Domains Using Generative Adversarial Networks},
author = {{S. Sankaranarayanan} and {Y. Balaji} and {C. Castillo} and {R. Chellappa}},
year = 2017,
month = {4},
booktitle = {2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition},
url = {https://www.semanticscholar.org/paper/15168665f4b8eb11466086e69780ed98e5280059},
}

R. Chellappa and Vishal M. Patel, “Sparse and Low-Rank Models for Visual Domain Adaptation.” 2017.
[BibTeX] [Link]

@inproceedings{63888267,
title = {Sparse and Low-Rank Models for Visual Domain Adaptation},
author = {{R. Chellappa} and {Vishal M. Patel}},
year = 2017,
month = {2},
booktitle = {},
url = {https://www.semanticscholar.org/paper/a790087e0d639450ed2d660505d17bf609217e31},
}

N. García, J. C. Vásquez-Correa, J. Orozco-Arroyave, N. Dehak, and Elmar Nöth, “Language Independent Assessment of Motor Impairments of Patients with Parkinson’s Disease Using i-Vectors,” in International Conference on Text, Speech and Dialogue, 2017.
[BibTeX] [Link]

@inproceedings{27064730,
title = {Language Independent Assessment of Motor Impairments of Patients with Parkinson's Disease Using i-Vectors},
author = {{N. García} and {J. C. Vásquez-Correa} and {J. Orozco-Arroyave} and {N. Dehak} and {Elmar Nöth}},
year = 2017,
month = {8},
booktitle = {International Conference on Text, Speech and Dialogue},
url = {https://www.semanticscholar.org/paper/d575b3672852ddc663f598b77d1209af8fc6eb43},
}

J. C. Vásquez-Correa, J. Orozco-Arroyave, R. Arora, Elmar Nöth, N. Dehak, H. Christensen, Frank Rudzicz, T. Bocklet, M. Cernak, H. Chinaei, J. Hannink, P. S. Nidadavolu, Maria Yancheva, A. Vann, and Nikolai Vogler, “Multi-view representation learning via gcca for multimodal analysis of Parkinson’s disease,” in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2017.
[BibTeX] [Link]

@inproceedings{11858941,
title = {Multi-view representation learning via gcca for multimodal analysis of Parkinson's disease},
author = {{J. C. Vásquez-Correa} and {J. Orozco-Arroyave} and {R. Arora} and {Elmar Nöth} and {N. Dehak} and {H. Christensen} and {Frank Rudzicz} and {T. Bocklet} and {M. Cernak} and {H. Chinaei} and {J. Hannink} and {P. S. Nidadavolu} and {Maria Yancheva} and {A. Vann} and {Nikolai Vogler}},
year = 2017,
month = {2},
booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
url = {https://www.semanticscholar.org/paper/8ffd686ebfad702e253d390b51eeed9586a273c3},
}

J. Seo, Hani Bakhshaee, Guillaume Garreau, Chi Zhu, A. Andreou, W. R. Thompson, and R. Mittal, “A method for the computational modeling of the physics of heart murmurs,” in Journal of Computational Physics, 2017.
[BibTeX] [Link]

@inproceedings{11218912,
title = {A method for the computational modeling of the physics of heart murmurs},
author = {{J. Seo} and {Hani Bakhshaee} and {Guillaume Garreau} and {Chi Zhu} and {A. Andreou} and {W. R. Thompson} and {R. Mittal}},
year = 2017,
month = {5},
booktitle = {Journal of Computational Physics},
url = {https://www.semanticscholar.org/paper/77821c70aa80e73313bbbc3c9896adeca0df1f5d},
}

J. Ayers, E. Leas, Jon-Patrick Allem, Adrian Benton, Mark Dredze, B. Althouse, T. Cruz, and J. Unger, “Why do people use electronic nicotine delivery systems (electronic cigarettes)? A content analysis of Twitter, 2012-2015,” in PLoS ONE, 2017.
[BibTeX] [Link]

@inproceedings{8487752,
title = {Why do people use electronic nicotine delivery systems (electronic cigarettes)? A content analysis of Twitter, 2012-2015},
author = {{J. Ayers} and {E. Leas} and {Jon-Patrick Allem} and {Adrian Benton} and {Mark Dredze} and {B. Althouse} and {T. Cruz} and {J. Unger}},
year = 2017,
month = {3},
booktitle = {PLoS ONE},
url = {https://www.semanticscholar.org/paper/5c60a417ae333a4503f0f4642bed9f66d3264ff6},
}

J. Craley, Thomas S. Murray, Daniel R. Mendat, and A. Andreou, “Action recognition using micro-Doppler signatures and a recurrent neural network,” in Annual Conference on Information Sciences and Systems, 2017.
[BibTeX] [Link]

@inproceedings{10284876,
title = {Action recognition using micro-Doppler signatures and a recurrent neural network},
author = {{J. Craley} and {Thomas S. Murray} and {Daniel R. Mendat} and {A. Andreou}},
year = 2017,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/12f53753de45f344606bb9e6f048d2a924aa7248},
}

Chandler May, Kevin Duh, Benjamin Van Durme, and Ashwin Lall, “Streaming Word Embeddings with the Space-Saving Algorithm,” in arXiv.org, 2017.
[BibTeX] [Link]

@inproceedings{19464052,
title = {Streaming Word Embeddings with the Space-Saving Algorithm},
author = {{Chandler May} and {Kevin Duh} and {Benjamin Van Durme} and {Ashwin Lall}},
year = 2017,
month = {4},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/ef6fea9d88aa763460b6cf48b2f60d23c6e60e9c},
}

Sayantan Sarkar, Ankan Bansal, U. Mahbub, and R. Chellappa, “UPSET and ANGRI : Breaking High Performance Image Classifiers,” in arXiv.org, 2017.
[BibTeX] [Link]

@inproceedings{20270268,
title = {UPSET and ANGRI : Breaking High Performance Image Classifiers},
author = {{Sayantan Sarkar} and {Ankan Bansal} and {U. Mahbub} and {R. Chellappa}},
year = 2017,
month = {7},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/defdab5b6a3ca1ac1d2bfa472c5a1cd69fc84d68},
}

Frances Yung, Kevin Duh, T. Komura, and Yuji Matsumoto, “A Psycholinguistic Model for the Marking of Discourse Relations,” in Dialogue and Discourse, 2017.
[BibTeX] [Link]

@inproceedings{32242456,
title = {A Psycholinguistic Model for the Marking of Discourse Relations},
author = {{Frances Yung} and {Kevin Duh} and {T. Komura} and {Yuji Matsumoto}},
year = 2017,
month = {1},
booktitle = {Dialogue and Discourse},
url = {https://www.semanticscholar.org/paper/9c95830fe00c4119234c5c1861b4145a2685e72b},
}

Kaiqi Huang, T. Tan, S. Maybank, R. Chellappa, and Jake Aggarval, “Guest Editorial Introduction to the Special Issue on Large-Scale Video Analytics for Enhanced Security: Algorithms and Systems,” in IEEE Transactions on Systems, Man & Cybernetics. Systems, 2017.
[BibTeX] [Link]

@inproceedings{45442934,
title = {Guest Editorial Introduction to the Special Issue on Large-Scale Video Analytics for Enhanced Security: Algorithms and Systems},
author = {{Kaiqi Huang} and {T. Tan} and {S. Maybank} and {R. Chellappa} and {Jake Aggarval}},
year = 2017,
month = {4},
booktitle = {IEEE Transactions on Systems, Man & Cybernetics. Systems},
url = {https://www.semanticscholar.org/paper/fa36668238e27ccccb000a79ac42fad19f93de68},
}

M. Cernak, Elmar Nöth, Frank Rudzicz, H. Christensen, J. Orozco-Arroyave, R. Arora, T. Bocklet, H. Chinaei, J. Hannink, P. S. Nidadavolu, J. C. Vásquez-Correa, Maria Yancheva, A. Vann, and Nikolai Vogler, “On the impact of non-modal phonation on phonological features,” in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2017.
[BibTeX] [Link]

@inproceedings{7535022,
title = {On the impact of non-modal phonation on phonological features},
author = {{M. Cernak} and {Elmar Nöth} and {Frank Rudzicz} and {H. Christensen} and {J. Orozco-Arroyave} and {R. Arora} and {T. Bocklet} and {H. Chinaei} and {J. Hannink} and {P. S. Nidadavolu} and {J. C. Vásquez-Correa} and {Maria Yancheva} and {A. Vann} and {Nikolai Vogler}},
year = 2017,
month = {3},
booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
url = {https://www.semanticscholar.org/paper/9cb2608434ce49e10837555b94f1381b3bd6f5e9},
}

Allyson Ettinger, Spandana Gella, Matthieu Labeau, Cecilia Ovesdotter Alm, Marine Carpuat, and Mark Dredze, “Proceedings of ACL 2017, Student Research Workshop,” in Annual Meeting of the Association for Computational Linguistics, 2017.
[BibTeX] [Link]

@inproceedings{195974347,
title = {Proceedings of ACL 2017, Student Research Workshop},
author = {{Allyson Ettinger} and {Spandana Gella} and {Matthieu Labeau} and {Cecilia Ovesdotter Alm} and {Marine Carpuat} and {Mark Dredze}},
year = 2017,
booktitle = {Annual Meeting of the Association for Computational Linguistics},
url = {https://www.semanticscholar.org/paper/d89918edf45d255da45661636752c8b8a3d0b3f2},
}

U. Mahbub, Sayantan Sarkar, and R. Chellappa, “Partial Face Detection in the Mobile Domain,” in Image and Vision Computing, 2017.
[BibTeX] [Link]

@inproceedings{6077228,
title = {Partial Face Detection in the Mobile Domain},
author = {{U. Mahbub} and {Sayantan Sarkar} and {R. Chellappa}},
year = 2017,
month = {4},
booktitle = {Image and Vision Computing},
url = {https://www.semanticscholar.org/paper/74ba4ab407b90592ffdf884a20e10006d2223015},
}

Amit Kumar, A. Alavi, and R. Chellappa, “KEPLER: Keypoint and Pose Estimation of Unconstrained Faces by Learning Efficient H-CNN Regressors,” in IEEE International Conference on Automatic Face & Gesture Recognition, 2017.
[BibTeX] [Link]

@inproceedings{9636241,
title = {KEPLER: Keypoint and Pose Estimation of Unconstrained Faces by Learning Efficient H-CNN Regressors},
author = {{Amit Kumar} and {A. Alavi} and {R. Chellappa}},
year = 2017,
month = {2},
booktitle = {IEEE International Conference on Automatic Face & Gesture Recognition},
url = {https://www.semanticscholar.org/paper/f7824758800a7b1a386db5bd35f84c81454d017a},
}

U. Mahbub, Sayantan Sarkar, and R. Chellappa, “Pooling Facial Segments to Face: The Shallow and Deep Ends,” in IEEE International Conference on Automatic Face & Gesture Recognition, 2017.
[BibTeX] [Link]

@inproceedings{10365029,
title = {Pooling Facial Segments to Face: The Shallow and Deep Ends},
author = {{U. Mahbub} and {Sayantan Sarkar} and {R. Chellappa}},
year = 2017,
month = {1},
booktitle = {IEEE International Conference on Automatic Face & Gesture Recognition},
url = {https://www.semanticscholar.org/paper/40c8cffd5aac68f59324733416b6b2959cb668fd},
}

Sheng Zhang, Kevin Duh, and Benjamin Van Durme, “Extraction with Neural Sequence-to-Sequence Models.” 2017.
[BibTeX] [Link]

@inproceedings{35809056,
title = {Extraction with Neural Sequence-to-Sequence Models},
author = {{Sheng Zhang} and {Kevin Duh} and {Benjamin Van Durme}},
year = 2017,
booktitle = {},
url = {https://www.semanticscholar.org/paper/5bd7012eb3d843e0825995a36a127756fdb45b80},
}

A. Nastasi, Tyler S Bryant, J. Canner, Mark Dredze, Melissa Camp, and Neeraja Nagarajan, “Breast Cancer Screening and Social Media: a Content Analysis of Evidence Use and Guideline Opinions on Twitter,” in Journal of Cancer Education, 2017.
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title = {Breast Cancer Screening and Social Media: a Content Analysis of Evidence Use and Guideline Opinions on Twitter},
author = {{A. Nastasi} and {Tyler S Bryant} and {J. Canner} and {Mark Dredze} and {Melissa Camp} and {Neeraja Nagarajan}},
year = 2017,
month = {1},
booktitle = {Journal of Cancer Education},
url = {https://www.semanticscholar.org/paper/269ed245822fe31c0cfedd8cd3cda2764e98f118},
}

Navaneeth Bodla, Bharat Singh, R. Chellappa, and L. Davis, “Soft-NMS — Improving Object Detection with One Line of Code,” in IEEE International Conference on Computer Vision, 2017.
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@inproceedings{15155826,
title = {Soft-NMS — Improving Object Detection with One Line of Code},
author = {{Navaneeth Bodla} and {Bharat Singh} and {R. Chellappa} and {L. Davis}},
year = 2017,
month = {4},
booktitle = {IEEE International Conference on Computer Vision},
url = {https://www.semanticscholar.org/paper/53c0aa8d33d240197caff824a6225fb223c1181c},
}

Sumit Shekhar, Vishal M. Patel, and R. Chellappa, “Synthesis-based Robust Low Resolution Face Recognition,” in arXiv.org, 2017.
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@inproceedings{16471250,
title = {Synthesis-based Robust Low Resolution Face Recognition},
author = {{Sumit Shekhar} and {Vishal M. Patel} and {R. Chellappa}},
year = 2017,
month = {7},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/a49df923dde393e4ee84102408100ed9350db53a},
}

Ching-Hui Chen and R. Chellappa, “Face Recognition Using an Outdoor Camera Network.” 2017.
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@inproceedings{63309829,
title = {Face Recognition Using an Outdoor Camera Network},
author = {{Ching-Hui Chen} and {R. Chellappa}},
year = 2017,
booktitle = {},
url = {https://www.semanticscholar.org/paper/350e5e5d9ea1dd52668d52d7b94e8b11424985b6},
}

Amit Kumar and R. Chellappa, “A Convolution Tree with Deconvolution Branches: Exploiting Geometric Relationships for Single Shot Keypoint Detection,” in arXiv.org, 2017.
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@inproceedings{1987224,
title = {A Convolution Tree with Deconvolution Branches: Exploiting Geometric Relationships for Single Shot Keypoint Detection},
author = {{Amit Kumar} and {R. Chellappa}},
year = 2017,
month = {4},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/1389ba6c3ff34cdf452ede130c738f37dca7e8cb},
}

He Zhang, Vishal M. Patel, and R. Chellappa, “Low-Rank and Joint Sparse Representations for Multi-Modal Recognition,” in IEEE Transactions on Image Processing, 2017.
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@inproceedings{27377753,
title = {Low-Rank and Joint Sparse Representations for Multi-Modal Recognition},
author = {{He Zhang} and {Vishal M. Patel} and {R. Chellappa}},
year = 2017,
month = {6},
booktitle = {IEEE Transactions on Image Processing},
url = {https://www.semanticscholar.org/paper/47197819a17c11c88ee2f262600e3bd6c20e3d34},
}

Michael C. Smith, Mark Dredze, S. Quinn, and David A. Broniatowski, “Monitoring Real-time Spatial Public Health Discussions in the Context of Vaccine Hesitancy,” in SMM4H@AMIA, 2017.
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@inproceedings{21953546,
title = {Monitoring Real-time Spatial Public Health Discussions in the Context of Vaccine Hesitancy},
author = {{Michael C. Smith} and {Mark Dredze} and {S. Quinn} and {David A. Broniatowski}},
year = 2017,
booktitle = {SMM4H@AMIA},
url = {https://www.semanticscholar.org/paper/07e5af29b9c2c6de4e4bd4334b68510e0e7826ef},
}

Mahyar Najibi, Pouya Samangouei, R. Chellappa, and L. Davis, “SSH: Single Stage Headless Face Detector,” in IEEE International Conference on Computer Vision, 2017.
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@inproceedings{3197876,
title = {SSH: Single Stage Headless Face Detector},
author = {{Mahyar Najibi} and {Pouya Samangouei} and {R. Chellappa} and {L. Davis}},
year = 2017,
month = {8},
booktitle = {IEEE International Conference on Computer Vision},
url = {https://www.semanticscholar.org/paper/a896ddeb0d253739c9aaef7fc1f170a2ba8407d3},
}

Travis Wolfe, Mark Dredze, and Benjamin Van Durme, “Feature Generation for Robust Semantic Role Labeling,” in arXiv.org, 2017.
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@inproceedings{15368453,
title = {Feature Generation for Robust Semantic Role Labeling},
author = {{Travis Wolfe} and {Mark Dredze} and {Benjamin Van Durme}},
year = 2017,
month = {2},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/6ec6c2c9a03ad960bd4b23f4281a6a19d9c900be},
}

Leonardo Badino, Luca Franceschi, R. Arora, Michele Donini, and M. Pontil, “A Speaker Adaptive DNN Training Approach for Speaker-Independent Acoustic Inversion,” in Interspeech, 2017.
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title = {A Speaker Adaptive DNN Training Approach for Speaker-Independent Acoustic Inversion},
author = {{Leonardo Badino} and {Luca Franceschi} and {R. Arora} and {Michele Donini} and {M. Pontil}},
year = 2017,
month = {8},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/47449a33b7b0eac650349b905b5a107780d7ba46},
}

Charbel G. Rizk, Francisco Tejada, J. Hughes, David Barbehenn, P. Pouliquen, and A. Andreou, “Characterization of RTN noise in the analog front-end of digital pixel imagers,” in International Symposium on Circuits and Systems, 2017.
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title = {Characterization of RTN noise in the analog front-end of digital pixel imagers},
author = {{Charbel G. Rizk} and {Francisco Tejada} and {J. Hughes} and {David Barbehenn} and {P. Pouliquen} and {A. Andreou}},
year = 2017,
month = {5},
booktitle = {International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/1552d2dab3995244ca13bc99e5ce0870759da33a},
}

Kate D. Fischl, Kaitlin L. Fair, Wei-Yu Tsai, J. Sampson, and A. Andreou, “Spike propagation path planning on IBM TrueNorth neurosynaptic system,” in Electronics Letters, 2017.
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title = {Spike propagation path planning on IBM TrueNorth neurosynaptic system},
author = {{Kate D. Fischl} and {Kaitlin L. Fair} and {Wei-Yu Tsai} and {J. Sampson} and {A. Andreou}},
year = 2017,
month = {6},
booktitle = {Electronics Letters},
url = {https://www.semanticscholar.org/paper/1cf2cb7cb959a05d611a22a8e3f90bdbb2b128c9},
}

Hui Ding, K. Sricharan, and R. Chellappa, “ExprGAN: Facial Expression Editing with Controllable Expression Intensity,” in AAAI Conference on Artificial Intelligence, 2017.
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title = {ExprGAN: Facial Expression Editing with Controllable Expression Intensity},
author = {{Hui Ding} and {K. Sricharan} and {R. Chellappa}},
year = 2017,
month = {9},
booktitle = {AAAI Conference on Artificial Intelligence},
url = {https://www.semanticscholar.org/paper/98ba5933d7fe9fec0f3b39d7072662007ca6a57e},
}

Ching-Hui Chen, Vishal M. Patel, and R. Chellappa, “Learning from Ambiguously Labeled Face Images,” in IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017.
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@inproceedings{2313547,
title = {Learning from Ambiguously Labeled Face Images},
author = {{Ching-Hui Chen} and {Vishal M. Patel} and {R. Chellappa}},
year = 2017,
month = {2},
booktitle = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
url = {https://www.semanticscholar.org/paper/58fc54590eb587c7227545fe85ec7d479a224fb7},
}

Ann Irvine and Mark Dredze, “Harmonic Grammar, Optimality Theory, and Syntax Learnability: An Empirical Exploration of Czech Word Order,” in arXiv.org, 2017.
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title = {Harmonic Grammar, Optimality Theory, and Syntax Learnability: An Empirical Exploration of Czech Word Order},
author = {{Ann Irvine} and {Mark Dredze}},
year = 2017,
month = {2},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/1d5028e2babab3e407a55e560f81057a5ebe76f7},
}

Hui Ding, Hao Zhou, S. Zhou, and R. Chellappa, “A Deep Cascade Network for Unaligned Face Attribute Classification,” in AAAI Conference on Artificial Intelligence, 2017.
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@inproceedings{19231876,
title = {A Deep Cascade Network for Unaligned Face Attribute Classification},
author = {{Hui Ding} and {Hao Zhou} and {S. Zhou} and {R. Chellappa}},
year = 2017,
month = {9},
booktitle = {AAAI Conference on Artificial Intelligence},
url = {https://www.semanticscholar.org/paper/7a16f37ecccca4f9703ce190dc596149b4ccc8d2},
}

R. Rudinger, K. Duh, and B. Van Durme, “Skip-Prop: Representing Sentences with One Vector Per Proposition,” in Proceedings of the 12th International Conference on Computational Semantics (IWCS) –- Short papers, 2017.
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@inproceedings{rudinger-etal-2017-skip,
title = "Skip-Prop: Representing Sentences with One Vector Per Proposition",
author = "Rudinger, Rachel and
Duh, Kevin and
Van Durme, Benjamin",
editor = "Gardent, Claire and
Retor{\'e}, Christian",
booktitle = "Proceedings of the 12th International Conference on Computational Semantics ({IWCS}) {---} Short papers",
year = "2017",
url = "https://aclanthology.org/W17-6936",
}

Wei-An Lin, Jun-Cheng Chen, and R. Chellappa, “A Proximity-Aware Hierarchical Clustering of Faces,” in IEEE International Conference on Automatic Face & Gesture Recognition, 2017.
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@inproceedings{1018804,
title = {A Proximity-Aware Hierarchical Clustering of Faces},
author = {{Wei-An Lin} and {Jun-Cheng Chen} and {R. Chellappa}},
year = 2017,
month = {3},
booktitle = {IEEE International Conference on Automatic Face & Gesture Recognition},
url = {https://www.semanticscholar.org/paper/b6f758be954d34817d4ebaa22b30c63a4b8ddb35},
}

R. Arora, T. V. Marinov, Poorya Mianjy, and N. Srebro, “Stochastic Approximation for Canonical Correlation Analysis,” in Neural Information Processing Systems, 2017.
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title = {Stochastic Approximation for Canonical Correlation Analysis},
author = {{R. Arora} and {T. V. Marinov} and {Poorya Mianjy} and {N. Srebro}},
year = 2017,
month = {2},
booktitle = {Neural Information Processing Systems},
url = {https://www.semanticscholar.org/paper/4ee4f802dac83bb99b98c09e41a8246a7e218826},
}

S. Sankaranarayanan, Arpit Jain, R. Chellappa, and Ser-Nam Lim, “Regularizing deep networks using efficient layerwise adversarial training,” in AAAI Conference on Artificial Intelligence, 2017.
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@inproceedings{19243741,
title = {Regularizing deep networks using efficient layerwise adversarial training},
author = {{S. Sankaranarayanan} and {Arpit Jain} and {R. Chellappa} and {Ser-Nam Lim}},
year = 2017,
month = {5},
booktitle = {AAAI Conference on Artificial Intelligence},
url = {https://www.semanticscholar.org/paper/68409946aa855b9a14de341bd321c38762817122},
}

Jingxiao Zheng, Vishal M. Patel, and R. Chellappa, “Recent Developments in Video-Based Face Recognition,” in Handbook of Biometrics for Forensic Science, 2017.
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@inproceedings{64154954,
title = {Recent Developments in Video-Based Face Recognition},
author = {{Jingxiao Zheng} and {Vishal M. Patel} and {R. Chellappa}},
year = 2017,
booktitle = {Handbook of Biometrics for Forensic Science},
url = {https://www.semanticscholar.org/paper/b241ea25eb7ca0a94a46c0b2800a661609fb82bf},
}

Mohammed E. Fathy and R. Chellappa, “Image Set Classification Using Sparse Bayesian Regression,” in IEEE Workshop/Winter Conference on Applications of Computer Vision, 2017.
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@inproceedings{7321504,
title = {Image Set Classification Using Sparse Bayesian Regression},
author = {{Mohammed E. Fathy} and {R. Chellappa}},
year = 2017,
month = {3},
booktitle = {IEEE Workshop/Winter Conference on Applications of Computer Vision},
url = {https://www.semanticscholar.org/paper/34c1e9a6166f4732d1738db803467f7abc47ba87},
}

X. Lan, P. Yuen, and R. Chellappa, “Robust MIL-Based Feature Template Learning for Object Tracking,” in AAAI Conference on Artificial Intelligence, 2017.
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@inproceedings{2131711,
title = {Robust MIL-Based Feature Template Learning for Object Tracking},
author = {{X. Lan} and {P. Yuen} and {R. Chellappa}},
year = 2017,
month = {2},
booktitle = {AAAI Conference on Artificial Intelligence},
url = {https://www.semanticscholar.org/paper/f03054e94c013780d17bd4a6bfbcbec8bdd44938},
}

Heng Zhang, Vishal M. Patel, and R. Chellappa, “Hierarchical Multimodal Metric Learning for Multimodal Classification,” in Computer Vision and Pattern Recognition, 2017.
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@inproceedings{206595370,
title = {Hierarchical Multimodal Metric Learning for Multimodal Classification},
author = {{Heng Zhang} and {Vishal M. Patel} and {R. Chellappa}},
year = 2017,
month = {7},
booktitle = {Computer Vision and Pattern Recognition},
url = {https://www.semanticscholar.org/paper/ea8805ce575f45630e02ac3760643db19d2e37b7},
}

Christopher Reale, Hyungtae Lee, H. Kwon, and R. Chellappa, “Deep Network Shrinkage Applied to Cross-Spectrum Face Recognition,” in IEEE International Conference on Automatic Face & Gesture Recognition, 2017.
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@inproceedings{5488683,
title = {Deep Network Shrinkage Applied to Cross-Spectrum Face Recognition},
author = {{Christopher Reale} and {Hyungtae Lee} and {H. Kwon} and {R. Chellappa}},
year = 2017,
month = {5},
booktitle = {IEEE International Conference on Automatic Face & Gesture Recognition},
url = {https://www.semanticscholar.org/paper/01e14d8ffd6767336d50c2b817a7b7744903e567},
}

N. García, J. Orozco-Arroyave, L. F. D’Haro, N. Dehak, and Elmar Nöth, “Evaluation of the Neurological State of People with Parkinson’s Disease Using i-Vectors,” in Interspeech, 2017.
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@inproceedings{31593134,
title = {Evaluation of the Neurological State of People with Parkinson's Disease Using i-Vectors},
author = {{N. García} and {J. Orozco-Arroyave} and {L. F. D’Haro} and {N. Dehak} and {Elmar Nöth}},
year = 2017,
month = {8},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/edad4b36bf583c4949dd2f1272b143309f300bcd},
}

Rajeev Ranjan, C. Castillo, and R. Chellappa, “L2-constrained Softmax Loss for Discriminative Face Verification,” in arXiv.org, 2017.
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@inproceedings{2524204,
title = {L2-constrained Softmax Loss for Discriminative Face Verification},
author = {{Rajeev Ranjan} and {C. Castillo} and {R. Chellappa}},
year = 2017,
month = {3},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/57a807f65e61bbba0ea3ba02572cc5843ecef2b6},
}

Kota Hara, Raviteja Vemulapalli, and R. Chellappa, “Designing Deep Convolutional Neural Networks for Continuous Object Orientation Estimation,” in arXiv.org, 2017.
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@inproceedings{16095257,
title = {Designing Deep Convolutional Neural Networks for Continuous Object Orientation Estimation},
author = {{Kota Hara} and {Raviteja Vemulapalli} and {R. Chellappa}},
year = 2017,
month = {2},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/a22c372911680793c7f94e3fd0b3843a2019f085},
}

Kota Hara and R. Chellappa, “Growing Regression Tree Forests by Classification for Continuous Object Pose Estimation,” in International Journal of Computer Vision, 2017.
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@inproceedings{20825989,
title = {Growing Regression Tree Forests by Classification for Continuous Object Pose Estimation},
author = {{Kota Hara} and {R. Chellappa}},
year = 2017,
month = {4},
booktitle = {International Journal of Computer Vision},
url = {https://www.semanticscholar.org/paper/63f2d43d7407931fa6f5ceb3c901b4d4ec11fbcd},
}

Xiaoyi Wu, Kevin Duh, and Yuji Matsumoto, “Generalized Hierarchical Word Sequence Framework for Language Modeling,” in Journal of Information Processing, 2017.
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@inproceedings{67020030,
title = {Generalized Hierarchical Word Sequence Framework for Language Modeling},
author = {{Xiaoyi Wu} and {Kevin Duh} and {Yuji Matsumoto}},
year = 2017,
month = {6},
booktitle = {Journal of Information Processing},
url = {https://www.semanticscholar.org/paper/129b987bc135db38a44995da420ca4146c6c2674},
}

Daniel R. Mendat, J. West, Sudarshan Ramenahalli, E. Niebur, and A. Andreou, “Audio-Visual beamforming with the Eigenmike microphone array an omni-camera and cognitive auditory features,” in Annual Conference on Information Sciences and Systems, 2017.
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title = {Audio-Visual beamforming with the Eigenmike microphone array an omni-camera and cognitive auditory features},
author = {{Daniel R. Mendat} and {J. West} and {Sudarshan Ramenahalli} and {E. Niebur} and {A. Andreou}},
year = 2017,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/b267c7bdb63305468a586f1142f5bac0c308765a},
}

Kate D. Fischl, Gaspar Tognetti, Daniel R. Mendat, G. Orchard, J. Rattray, Christos Sapsanis, Laura F. Campbell, Laxaviera Elphage, T. Niebur, Alejandro Pasciaroni, V. Rennoll, Heather Romney, Shamaria Walker, P. Pouliquen, and A. Andreou, “Neuromorphic self-driving robot with retinomorphic vision and spike-based processing/closed-loop control,” in Annual Conference on Information Sciences and Systems, 2017.
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@inproceedings{27805933,
title = {Neuromorphic self-driving robot with retinomorphic vision and spike-based processing/closed-loop control},
author = {{Kate D. Fischl} and {Gaspar Tognetti} and {Daniel R. Mendat} and {G. Orchard} and {J. Rattray} and {Christos Sapsanis} and {Laura F. Campbell} and {Laxaviera Elphage} and {T. Niebur} and {Alejandro Pasciaroni} and {V. Rennoll} and {Heather Romney} and {Shamaria Walker} and {P. Pouliquen} and {A. Andreou}},
year = 2017,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/4cdaf34f9e01fbb577bdd66296b8afb1b2110f58},
}

Kate D. Fischl, Kaitlin L. Fair, Wei-Yu Tsai, J. Sampson, and A. Andreou, “Path planning on the TrueNorth neurosynaptic system,” in International Symposium on Circuits and Systems, 2017.
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@inproceedings{19618329,
title = {Path planning on the TrueNorth neurosynaptic system},
author = {{Kate D. Fischl} and {Kaitlin L. Fair} and {Wei-Yu Tsai} and {J. Sampson} and {A. Andreou}},
year = 2017,
month = {5},
booktitle = {International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/b3771178abbc7a6d5a244a58cb799a776cbe57d2},
}

Santosh Kesiraju, R. Pappagari, Lucas Ondel, L. Burget, N. Dehak, S. Khudanpur, J. Černocký, and S. Gangashetty, “Topic identification of spoken documents using unsupervised acoustic unit discovery,” in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2017.
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title = {Topic identification of spoken documents using unsupervised acoustic unit discovery},
author = {{Santosh Kesiraju} and {R. Pappagari} and {Lucas Ondel} and {L. Burget} and {N. Dehak} and {S. Khudanpur} and {J. Černocký} and {S. Gangashetty}},
year = 2017,
month = {3},
booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
url = {https://www.semanticscholar.org/paper/2e8d47fcba60cff5cf5ba9aa535192cccfc37db1},
}

Jie Chen, Vishal M. Patel, Li Liu, Vili Kellokumpu, Guoying Zhao, M. Pietikäinen, and R. Chellappa, “Robust local features for remote face recognition,” in Image and Vision Computing, 2017.
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@inproceedings{27870062,
title = {Robust local features for remote face recognition},
author = {{Jie Chen} and {Vishal M. Patel} and {Li Liu} and {Vili Kellokumpu} and {Guoying Zhao} and {M. Pietikäinen} and {R. Chellappa}},
year = 2017,
month = {8},
booktitle = {Image and Vision Computing},
url = {https://www.semanticscholar.org/paper/9f0fff6c0dbc7ff9e0b03c7964a9d375d2724c1e},
}

Ching-Hui Chen, Jun-Cheng Chen, C. Castillo, and R. Chellappa, “Video-Based Face Association and Identification,” in IEEE International Conference on Automatic Face & Gesture Recognition, 2017.
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@inproceedings{12729945,
title = {Video-Based Face Association and Identification},
author = {{Ching-Hui Chen} and {Jun-Cheng Chen} and {C. Castillo} and {R. Chellappa}},
year = 2017,
month = {5},
booktitle = {IEEE International Conference on Automatic Face & Gesture Recognition},
url = {https://www.semanticscholar.org/paper/d6bdc70d259b38bbeb3a78db064232b4b4acc88f},
}

Graham Neubig, Chris Dyer, Yoav Goldberg, Austin Matthews, Waleed Ammar, Antonios Anastasopoulos, Miguel Ballesteros, David Chiang, Daniel Clothiaux, Trevor Cohn, Kevin Duh, Manaal Faruqui, Cynthia Gan, Dan Garrette, Yangfeng Ji, Lingpeng Kong, A. Kuncoro, Manish Kumar, Chaitanya Malaviya, Paul Michel, Yusuke Oda, Matthew Richardson, Naomi Saphra, Swabha Swayamdipta, and Pengcheng Yin, “DyNet: The Dynamic Neural Network Toolkit,” in arXiv.org, 2017.
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@inproceedings{2170930,
title = {DyNet: The Dynamic Neural Network Toolkit},
author = {{Graham Neubig} and {Chris Dyer} and {Yoav Goldberg} and {Austin Matthews} and {Waleed Ammar} and {Antonios Anastasopoulos} and {Miguel Ballesteros} and {David Chiang} and {Daniel Clothiaux} and {Trevor Cohn} and {Kevin Duh} and {Manaal Faruqui} and {Cynthia Gan} and {Dan Garrette} and {Yangfeng Ji} and {Lingpeng Kong} and {A. Kuncoro} and {Manish Kumar} and {Chaitanya Malaviya} and {Paul Michel} and {Yusuke Oda} and {Matthew Richardson} and {Naomi Saphra} and {Swabha Swayamdipta} and {Pengcheng Yin}},
year = 2017,
month = {1},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/480d545ac4a4ffff5b1bc291c2de613192e35d91},
}

Ankan Bansal, C. Castillo, Rajeev Ranjan, and R. Chellappa, “The Do’s and Don’ts for CNN-Based Face Verification,” in 2017 IEEE International Conference on Computer Vision Workshops (ICCVW), 2017.
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@inproceedings{9381465,
title = {The Do’s and Don’ts for CNN-Based Face Verification},
author = {{Ankan Bansal} and {C. Castillo} and {Rajeev Ranjan} and {R. Chellappa}},
year = 2017,
month = {5},
booktitle = {2017 IEEE International Conference on Computer Vision Workshops (ICCVW)},
url = {https://www.semanticscholar.org/paper/def2983576001bac7d6461d78451159800938112},
}

Mark Dredze, Zach Wood-Doughty, S. Quinn, and David A. Broniatowski, “Vaccine opponents’ use of Twitter during the 2016 US presidential election: Implications for practice and policy.,” in Vaccine, 2017.
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@inproceedings{38341631,
title = {Vaccine opponents' use of Twitter during the 2016 US presidential election: Implications for practice and policy.},
author = {{Mark Dredze} and {Zach Wood-Doughty} and {S. Quinn} and {David A. Broniatowski}},
year = 2017,
month = {8},
booktitle = {Vaccine},
url = {https://www.semanticscholar.org/paper/e08d39a6aa0fbe20a20654ca5ee4ef9d130cc0d3},
}

J. Villalba, N. Brümmer, and N. Dehak, “Tied Variational Autoencoder Backends for i-Vector Speaker Recognition,” in Interspeech, 2017.
[BibTeX] [Link]

@inproceedings{10319016,
title = {Tied Variational Autoencoder Backends for i-Vector Speaker Recognition},
author = {{J. Villalba} and {N. Brümmer} and {N. Dehak}},
year = 2017,
month = {8},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/4488cba0d06ae06b4b7b99cbb3639731c9eefe32},
}

Emily M. Hand and R. Chellappa, “Attributes for Improved Attributes: A Multi-Task Network Utilizing Implicit and Explicit Relationships for Facial Attribute Classification,” in AAAI Conference on Artificial Intelligence, 2017.
[BibTeX] [Link]

@inproceedings{19671339,
title = {Attributes for Improved Attributes: A Multi-Task Network Utilizing Implicit and Explicit Relationships for Facial Attribute Classification},
author = {{Emily M. Hand} and {R. Chellappa}},
year = 2017,
month = {2},
booktitle = {AAAI Conference on Artificial Intelligence},
url = {https://www.semanticscholar.org/paper/053931267af79a89791479b18d1b9cde3edcb415},
}

R. He, B. Lovell, R. Chellappa, Anil K. Jain, and Zhenan Sun, “Editorial: Special issue on ubiquitous biometrics,” in Pattern Recognition, 2017.
[BibTeX] [Link]

@inproceedings{57408,
title = {Editorial: Special issue on ubiquitous biometrics},
author = {{R. He} and {B. Lovell} and {R. Chellappa} and {Anil K. Jain} and {Zhenan Sun}},
year = 2017,
month = {6},
booktitle = {Pattern Recognition},
url = {https://www.semanticscholar.org/paper/5aac6f1f916286cc6c4749bf9f4a60fc3089da52},
}

Ke Wu, X. Li, Yanif Ahmad, V. Braverman, Randal Burns, Zachary Burwell, M. Dinitz, Mark Dredze, Abhishek Jain, and Philipp Koehn, “DETERMINISTIC CONSTRUCTION OF SYNCHRONIZATION STRING OVER SMALL ALPHABET.” 2017.
[BibTeX] [Link]

@inproceedings{54714125,
title = {DETERMINISTIC CONSTRUCTION OF SYNCHRONIZATION STRING OVER SMALL ALPHABET},
author = {{Ke Wu} and {X. Li} and {Yanif Ahmad} and {V. Braverman} and {Randal Burns} and {Zachary Burwell} and {M. Dinitz} and {Mark Dredze} and {Abhishek Jain} and {Philipp Koehn}},
year = 2017,
booktitle = {},
url = {https://www.semanticscholar.org/paper/72b9c8872c7c5a595a8ee6e41dffd7f91940d1f5},
}

Navaneeth Bodla, Jingxiao Zheng, Hongyu Xu, Jun-Cheng Chen, C. Castillo, and R. Chellappa, “Deep Heterogeneous Feature Fusion for Template-Based Face Recognition,” in IEEE Workshop/Winter Conference on Applications of Computer Vision, 2017.
[BibTeX] [Link]

@inproceedings{7597775,
title = {Deep Heterogeneous Feature Fusion for Template-Based Face Recognition},
author = {{Navaneeth Bodla} and {Jingxiao Zheng} and {Hongyu Xu} and {Jun-Cheng Chen} and {C. Castillo} and {R. Chellappa}},
year = 2017,
month = {2},
booktitle = {IEEE Workshop/Winter Conference on Applications of Computer Vision},
url = {https://www.semanticscholar.org/paper/f017e25b4269e88e077239f8d47777a779b624e8},
}

Pouya Samangouei, Vishal M. Patel, and R. Chellappa, “Facial attributes for active authentication on mobile devices,” in Image and Vision Computing, 2017.
[BibTeX] [Link]

@inproceedings{10810779,
title = {Facial attributes for active authentication on mobile devices},
author = {{Pouya Samangouei} and {Vishal M. Patel} and {R. Chellappa}},
year = 2017,
month = {2},
booktitle = {Image and Vision Computing},
url = {https://www.semanticscholar.org/paper/94a7c97d1e3eb5dbfb20b180780451486597a9be},
}

Ning Gao, Douglas W. Oard, and Mark Dredze, “Support for Interactive Identification of Mentioned Entities in Conversational Speech,” in Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2017.
[BibTeX] [Link]

@inproceedings{20125743,
title = {Support for Interactive Identification of Mentioned Entities in Conversational Speech},
author = {{Ning Gao} and {Douglas W. Oard} and {Mark Dredze}},
year = 2017,
month = {8},
booktitle = {Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
url = {https://www.semanticscholar.org/paper/b41d3eece00ba6b849b15cf2edd2417a410b8698},
}

Chunxi Liu, Jinyi Yang, Ming Sun, Santosh Kesiraju, Alena Rott, Lucas Ondel, Pegah Ghahremani, N. Dehak, L. Burget, and S. Khudanpur, “An empirical evaluation of zero resource acoustic unit discovery,” in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2017.
[BibTeX] [Link]

@inproceedings{2342176,
title = {An empirical evaluation of zero resource acoustic unit discovery},
author = {{Chunxi Liu} and {Jinyi Yang} and {Ming Sun} and {Santosh Kesiraju} and {Alena Rott} and {Lucas Ondel} and {Pegah Ghahremani} and {N. Dehak} and {L. Burget} and {S. Khudanpur}},
year = 2017,
month = {2},
booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
url = {https://www.semanticscholar.org/paper/ada0452efd5b0bc345de1bc66c875d0126c56d2c},
}

Michael J. Paul and Mark Dredze, “Social Monitoring for Public Health,” in Synthesis Lectures on Information Concepts Retrieval and Services, 2017.
[BibTeX] [Link]

@inproceedings{34317289,
title = {Social Monitoring for Public Health},
author = {{Michael J. Paul} and {Mark Dredze}},
year = 2017,
month = {8},
booktitle = {Synthesis Lectures on Information Concepts Retrieval and Services},
url = {https://www.semanticscholar.org/paper/80d6fb37be35edfa8a0395eb6334424132c6d07e},
}

Jon-Patrick Allem, E. Leas, Theodore L. Caputi, Mark Dredze, B. Althouse, S. Noar, and J. Ayers, “The Charlie Sheen Effect on Rapid In-home Human Immunodeficiency Virus Test Sales,” in Prevention Science, 2017.
[BibTeX] [Link]

@inproceedings{4416337,
title = {The Charlie Sheen Effect on Rapid In-home Human Immunodeficiency Virus Test Sales},
author = {{Jon-Patrick Allem} and {E. Leas} and {Theodore L. Caputi} and {Mark Dredze} and {B. Althouse} and {S. Noar} and {J. Ayers}},
year = 2017,
month = {5},
booktitle = {Prevention Science},
url = {https://www.semanticscholar.org/paper/867285873edc3186560e6783c5359b4d9b5e9982},
}

H. Qin, T. Shinozaki, and K. Duh, “Evolution Strategy Based Automatic Tuning of Neural Machine Translation Systems,” in Proceedings of the 14th International Conference on Spoken Language Translation, Tokyo, Japan, 2017, p. 120–128.
[BibTeX] [Abstract] [Link]

Neural machine translation (NMT) systems have demonstrated promising results in recent years. However, non-trivial amounts of manual effort are required for tuning network architectures, training configurations, and pre-processing settings such as byte pair encoding (BPE). In this study, we propose an evolution strategy based automatic tuning method for NMT. In particular, we apply the covariance matrix adaptation-evolution strategy (CMA-ES), and investigate a Pareto-based multi-objective CMA-ES to optimize the translation performance and computational time jointly. Experimental results show that the proposed method automatically finds NMT systems that outperform the initial manual setting.

@inproceedings{qin-etal-2017-evolution,
title = "Evolution Strategy Based Automatic Tuning of Neural Machine Translation Systems",
author = "Qin, Hao and
Shinozaki, Takahiro and
Duh, Kevin",
editor = "Sakti, Sakriani and
Utiyama, Masao",
booktitle = "Proceedings of the 14th International Conference on Spoken Language Translation",
month = dec # " 14-15",
year = "2017",
address = "Tokyo, Japan",
publisher = "International Workshop on Spoken Language Translation",
url = "https://aclanthology.org/2017.iwslt-1.17",
pages = "120--128",
abstract = "Neural machine translation (NMT) systems have demonstrated promising results in recent years. However, non-trivial amounts of manual effort are required for tuning network architectures, training configurations, and pre-processing settings such as byte pair encoding (BPE). In this study, we propose an evolution strategy based automatic tuning method for NMT. In particular, we apply the covariance matrix adaptation-evolution strategy (CMA-ES), and investigate a Pareto-based multi-objective CMA-ES to optimize the translation performance and computational time jointly. Experimental results show that the proposed method automatically finds NMT systems that outperform the initial manual setting.",
}

Xiaolei Huang, Michael C. Smith, Michael J. Paul, D. Ryzhkov, S. Quinn, David A. Broniatowski, and Mark Dredze, “Examining Patterns of Influenza Vaccination in Social Media,” in AAAI Workshops, 2017.
[BibTeX] [Link]

@inproceedings{17885136,
title = {Examining Patterns of Influenza Vaccination in Social Media},
author = {{Xiaolei Huang} and {Michael C. Smith} and {Michael J. Paul} and {D. Ryzhkov} and {S. Quinn} and {David A. Broniatowski} and {Mark Dredze}},
year = 2017,
booktitle = {AAAI Workshops},
url = {https://www.semanticscholar.org/paper/81202a14ed728c3d8fa8224f239c526da0c57fba},
}

P. Torres-Carrasquillo, Fred Richardson, S. Nercessian, D. Sturim, W. Campbell, Youngjune Gwon, Swaroop Vattam, N. Dehak, Sri Harish Reddy Mallidi, P. S. Nidadavolu, Ruizhi Li, and Réda Dehak, “The MIT-LL, JHU and LRDE NIST 2016 Speaker Recognition Evaluation System,” in Interspeech, 2017.
[BibTeX] [Link]

@inproceedings{32850737,
title = {The MIT-LL, JHU and LRDE NIST 2016 Speaker Recognition Evaluation System},
author = {{P. Torres-Carrasquillo} and {Fred Richardson} and {S. Nercessian} and {D. Sturim} and {W. Campbell} and {Youngjune Gwon} and {Swaroop Vattam} and {N. Dehak} and {Sri Harish Reddy Mallidi} and {P. S. Nidadavolu} and {Ruizhi Li} and {Réda Dehak}},
year = 2017,
month = {8},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/d6c6f46725f538cf5960d3a4a21eea2e9605f3a8},
}

Boyu Lu, Jingxiao Zheng, Jun-Cheng Chen, and R. Chellappa, “Pose-Robust Face Verification by Exploiting Competing Tasks,” in IEEE Workshop/Winter Conference on Applications of Computer Vision, 2017.
[BibTeX] [Link]

@inproceedings{40336969,
title = {Pose-Robust Face Verification by Exploiting Competing Tasks},
author = {{Boyu Lu} and {Jingxiao Zheng} and {Jun-Cheng Chen} and {R. Chellappa}},
year = 2017,
month = {3},
booktitle = {IEEE Workshop/Winter Conference on Applications of Computer Vision},
url = {https://www.semanticscholar.org/paper/ec39e9c21d6e2576f21936b1ecc1574dadaf291e},
}

J. Orozco-Arroyave, J. C. Vásquez-Correa, J. Vargas-Bonilla, R. Arora, N. Dehak, P. S. Nidadavolu, H. Christensen, Frank Rudzicz, Maria Yancheva, H. Chinaei, A. Vann, Nikolai Vogler, T. Bocklet, M. Cernak, J. Hannink, and Elmar Nöth, “NeuroSpeech: An open-source software for Parkinson’s speech analysis,” in Digit. Signal Process., 2017.
[BibTeX] [Link]

@inproceedings{44116329,
title = {NeuroSpeech: An open-source software for Parkinson's speech analysis},
author = {{J. Orozco-Arroyave} and {J. C. Vásquez-Correa} and {J. Vargas-Bonilla} and {R. Arora} and {N. Dehak} and {P. S. Nidadavolu} and {H. Christensen} and {Frank Rudzicz} and {Maria Yancheva} and {H. Chinaei} and {A. Vann} and {Nikolai Vogler} and {T. Bocklet} and {M. Cernak} and {J. Hannink} and {Elmar Nöth}},
year = 2017,
month = {7},
booktitle = {Digit. Signal Process.},
url = {https://www.semanticscholar.org/paper/2b2f10ffb9b25b8fbc5a4d9c2ac4cd23b1cc0531},
}

J. Ayers, E. Leas, Mark Dredze, Jon-Patrick Allem, J. Grabowski, and Linda L. Hill, “Pokémon GO-A New Distraction for Drivers and Pedestrians.,” in JAMA Internal Medicine, 2016.
[BibTeX] [Link]

@inproceedings{45297221,
title = {Pokémon GO-A New Distraction for Drivers and Pedestrians.},
author = {{J. Ayers} and {E. Leas} and {Mark Dredze} and {Jon-Patrick Allem} and {J. Grabowski} and {Linda L. Hill}},
year = 2016,
month = {12},
booktitle = {JAMA Internal Medicine},
url = {https://www.semanticscholar.org/paper/2a22e1bd9be80a5390f46b0b522988d6d23ccafc},
}

Xingguo Li, Zhaoran Wang, Junwei Lu, R. Arora, Jarvis D. Haupt, Han Liu, and T. Zhao, “Symmetry, Saddle Points, and Global Geometry of Nonconvex Matrix Factorization,” in arXiv.org, 2016.
[BibTeX] [Link]

@inproceedings{17007149,
title = {Symmetry, Saddle Points, and Global Geometry of Nonconvex Matrix Factorization},
author = {{Xingguo Li} and {Zhaoran Wang} and {Junwei Lu} and {R. Arora} and {Jarvis D. Haupt} and {Han Liu} and {T. Zhao}},
year = 2016,
month = {12},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/efc0cc6f85bad1bc270b7405a8457ddd0506aa9b},
}

Christopher Reale, N. Nasrabadi, and R. Chellappa, “An analysis of the robustness of deep face recognition networks to noisy training labels,” in IEEE Global Conference on Signal and Information Processing, 2016.
[BibTeX] [Link]

@inproceedings{14936914,
title = {An analysis of the robustness of deep face recognition networks to noisy training labels},
author = {{Christopher Reale} and {N. Nasrabadi} and {R. Chellappa}},
year = 2016,
month = {12},
booktitle = {IEEE Global Conference on Signal and Information Processing},
url = {https://www.semanticscholar.org/paper/24e82eaf3257e761d6ca0ffcc2cbca30dfca82e9},
}

Tomohiro Tanaka, Takafumi Moriya, T. Shinozaki, Shinji Watanabe, Takaaki Hori, and Kevin Duh, “Automated structure discovery and parameter tuning of neural network language model based on evolution strategy,” in Spoken Language Technology Workshop, 2016.
[BibTeX] [Link]

@inproceedings{23524169,
title = {Automated structure discovery and parameter tuning of neural network language model based on evolution strategy},
author = {{Tomohiro Tanaka} and {Takafumi Moriya} and {T. Shinozaki} and {Shinji Watanabe} and {Takaaki Hori} and {Kevin Duh}},
year = 2016,
month = {12},
booktitle = {Spoken Language Technology Workshop},
url = {https://www.semanticscholar.org/paper/db0c587111cfed85dcea413e385b17881e6e0cbb},
}

Lee Stearns, U. Oh, Bridget J. Cheng, Leah Findlater, David Ross, R. Chellappa, and Jon E. Froehlich, “Localization of skin features on the hand and wrist from small image patches,” in International Conference on Pattern Recognition, 2016.
[BibTeX] [Link]

@inproceedings{1829184,
title = {Localization of skin features on the hand and wrist from small image patches},
author = {{Lee Stearns} and {U. Oh} and {Bridget J. Cheng} and {Leah Findlater} and {David Ross} and {R. Chellappa} and {Jon E. Froehlich}},
year = 2016,
month = {12},
booktitle = {International Conference on Pattern Recognition},
url = {https://www.semanticscholar.org/paper/ac4bc8c956fb8e1ed65f98d5ddeaf42b9bd6d699},
}

A. Andy, S. Sekine, M. Rwebangira, and M. Dredze, “Name Variation in Community Question Answering Systems,” in Proceedings of the 2nd Workshop on Noisy User-generated Text (WNUT), Osaka, Japan, 2016, p. 51–60.
[BibTeX] [Abstract] [Link]

Name Variation in Community Question Answering Systems Abstract Community question answering systems are forums where users can ask and answer questions in various categories. Examples are Yahoo! Answers, Quora, and Stack Overflow. A common challenge with such systems is that a significant percentage of asked questions are left unanswered. In this paper, we propose an algorithm to reduce the number of unanswered questions in Yahoo! Answers by reusing the answer to the most similar past resolved question to the unanswered question, from the site. Semantically similar questions could be worded differently, thereby making it difficult to find questions that have shared needs. For example, {“}Who is the best player for the Reds?{”} and {“}Who is currently the biggest star at Manchester United?{”} have a shared need but are worded differently; also, {“}Reds{”} and {“}Manchester United{”} are used to refer to the soccer team Manchester United football club. In this research, we focus on question categories that contain a large number of named entities and entity name variations. We show that in these categories, entity linking can be used to identify relevant past resolved questions with shared needs as a given question by disambiguating named entities and matching these questions based on the disambiguated entities, identified entities, and knowledge base information related to these entities. We evaluated our algorithm on a new dataset constructed from Yahoo! Answers. The dataset contains annotated question pairs, (Qgiven, [Qpast, Answer]). We carried out experiments on several question categories and show that an entity-based approach gives good performance when searching for similar questions in entity rich categories.

@inproceedings{andy-etal-2016-name,
title = "Name Variation in Community Question Answering Systems",
author = "Andy, Anietie and
Sekine, Satoshi and
Rwebangira, Mugizi and
Dredze, Mark",
editor = "Han, Bo and
Ritter, Alan and
Derczynski, Leon and
Xu, Wei and
Baldwin, Tim",
booktitle = "Proceedings of the 2nd Workshop on Noisy User-generated Text ({WNUT})",
month = dec,
year = "2016",
address = "Osaka, Japan",
publisher = "The COLING 2016 Organizing Committee",
url = "https://aclanthology.org/W16-3909",
pages = "51--60",
abstract = "Name Variation in Community Question Answering Systems Abstract Community question answering systems are forums where users can ask and answer questions in various categories. Examples are Yahoo! Answers, Quora, and Stack Overflow. A common challenge with such systems is that a significant percentage of asked questions are left unanswered. In this paper, we propose an algorithm to reduce the number of unanswered questions in Yahoo! Answers by reusing the answer to the most similar past resolved question to the unanswered question, from the site. Semantically similar questions could be worded differently, thereby making it difficult to find questions that have shared needs. For example, {``}Who is the best player for the Reds?{''} and {``}Who is currently the biggest star at Manchester United?{''} have a shared need but are worded differently; also, {``}Reds{''} and {``}Manchester United{''} are used to refer to the soccer team Manchester United football club. In this research, we focus on question categories that contain a large number of named entities and entity name variations. We show that in these categories, entity linking can be used to identify relevant past resolved questions with shared needs as a given question by disambiguating named entities and matching these questions based on the disambiguated entities, identified entities, and knowledge base information related to these entities. We evaluated our algorithm on a new dataset constructed from Yahoo! Answers. The dataset contains annotated question pairs, (Qgiven, [Qpast, Answer]). We carried out experiments on several question categories and show that an entity-based approach gives good performance when searching for similar questions in entity rich categories.",
}

Boyu Lu, Jun-Cheng Chen, and R. Chellappa, “Regularized metric adaptation for unconstrained face verification,” in International Conference on Pattern Recognition, 2016.
[BibTeX] [Link]

@inproceedings{662098,
title = {Regularized metric adaptation for unconstrained face verification},
author = {{Boyu Lu} and {Jun-Cheng Chen} and {R. Chellappa}},
year = 2016,
month = {12},
booktitle = {International Conference on Pattern Recognition},
url = {https://www.semanticscholar.org/paper/5865b6d83ba6dbbf9167f1481e9339c2ef1d1f6b},
}

Xingguo Li, Jarvis D. Haupt, Junwei Lu, Zhaoran Wang, R. Arora, Han Liu, and T. Zhao, “Symmetry, Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization,” in IEEE Transactions on Information Theory, 2016.
[BibTeX] [Link]

@inproceedings{52065722,
title = {Symmetry, Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization},
author = {{Xingguo Li} and {Jarvis D. Haupt} and {Junwei Lu} and {Zhaoran Wang} and {R. Arora} and {Han Liu} and {T. Zhao}},
year = 2016,
month = {12},
booktitle = {IEEE Transactions on Information Theory},
url = {https://www.semanticscholar.org/paper/cf853068cefee2d78d4dbccc8bca1ea450fc3377},
}

Arthita Ghosh and R. Chellappa, “Deep feature extraction in the DCT domain,” in International Conference on Pattern Recognition, 2016.
[BibTeX] [Link]

@inproceedings{33767866,
title = {Deep feature extraction in the DCT domain},
author = {{Arthita Ghosh} and {R. Chellappa}},
year = 2016,
month = {12},
booktitle = {International Conference on Pattern Recognition},
url = {https://www.semanticscholar.org/paper/d1a760d034200c0a34aa1dbdaa0620756c2aa5e8},
}

Lin F. Yang, R. Arora, V. Braverman, and T. Zhao, “The Physical Systems Behind Optimization Algorithms,” in Neural Information Processing Systems, 2016.
[BibTeX] [Link]

@inproceedings{15663225,
title = {The Physical Systems Behind Optimization Algorithms},
author = {{Lin F. Yang} and {R. Arora} and {V. Braverman} and {T. Zhao}},
year = 2016,
month = {12},
booktitle = {Neural Information Processing Systems},
url = {https://www.semanticscholar.org/paper/3fd96fe6f1ea5193536296f291aff00439eb9bbd},
}

Maya Kabkab, Emily M. Hand, and R. Chellappa, “On the size of Convolutional Neural Networks and generalization performance,” in International Conference on Pattern Recognition, 2016.
[BibTeX] [Link]

@inproceedings{11153595,
title = {On the size of Convolutional Neural Networks and generalization performance},
author = {{Maya Kabkab} and {Emily M. Hand} and {R. Chellappa}},
year = 2016,
month = {12},
booktitle = {International Conference on Pattern Recognition},
url = {https://www.semanticscholar.org/paper/3b092733f428b12f1f920638f868ed1e8663fe57},
}

Hongyu Xu, Jingjing Zheng, A. Alavi, and R. Chellappa, “Template regularized sparse coding for face verification,” in International Conference on Pattern Recognition, 2016.
[BibTeX] [Link]

@inproceedings{13374811,
title = {Template regularized sparse coding for face verification},
author = {{Hongyu Xu} and {Jingjing Zheng} and {A. Alavi} and {R. Chellappa}},
year = 2016,
month = {12},
booktitle = {International Conference on Pattern Recognition},
url = {https://www.semanticscholar.org/paper/8d3e95c31c93548b8c71dbeee2e9f7180067a888},
}

R. Chellappa, “The changing fortunes of pattern recognition and computer vision,” in Image and Vision Computing, 2016.
[BibTeX] [Link]

@inproceedings{12071891,
title = {The changing fortunes of pattern recognition and computer vision},
author = {{R. Chellappa}},
year = 2016,
month = {11},
booktitle = {Image and Vision Computing},
url = {https://www.semanticscholar.org/paper/c9434b58592e3e845262a3785012a042101ff547},
}

R. Knowles, J. Carroll, and M. Dredze, “Demographer: Extremely Simple Name Demographics,” in Proceedings of the First Workshop on NLP and Computational Social Science, Austin, Texas, 2016, p. 108–113. doi:10.18653/v1/W16-5614
[BibTeX] [Link]

@inproceedings{knowles-etal-2016-demographer,
title = "{D}emographer: Extremely Simple Name Demographics",
author = "Knowles, Rebecca and
Carroll, Josh and
Dredze, Mark",
editor = {Bamman, David and
Do{\u{g}}ru{\"o}z, A. Seza and
Eisenstein, Jacob and
Hovy, Dirk and
Jurgens, David and
O{'}Connor, Brendan and
Oh, Alice and
Tsur, Oren and
Volkova, Svitlana},
booktitle = "Proceedings of the First Workshop on {NLP} and Computational Social Science",
month = nov,
year = "2016",
address = "Austin, Texas",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W16-5614",
doi = "10.18653/v1/W16-5614",
pages = "108--113",
}

Tomohiro Tanaka, Takafumi Moriya, T. Shinozaki, Shinji Watanabe, Takaaki Hori, and Kevin Duh, “Evolutionary optimization of long short-term memory neural network language model,” in Journal of the Acoustical Society of America, 2016.
[BibTeX] [Link]

@inproceedings{125693048,
title = {Evolutionary optimization of long short-term memory neural network language model},
author = {{Tomohiro Tanaka} and {Takafumi Moriya} and {T. Shinozaki} and {Shinji Watanabe} and {Takaaki Hori} and {Kevin Duh}},
year = 2016,
month = {11},
booktitle = {Journal of the Acoustical Society of America},
url = {https://www.semanticscholar.org/paper/faa4468f2ad1c7cedaf04bf56ebb20ae4b349952},
}

Raviteja Vemulapalli, Felipe Arrate, and R. Chellappa, “R3DG features: Relative 3D geometry-based skeletal representations for human action recognition,” in Computer Vision and Image Understanding, 2016.
[BibTeX] [Link]

@inproceedings{11823644,
title = {R3DG features: Relative 3D geometry-based skeletal representations for human action recognition},
author = {{Raviteja Vemulapalli} and {Felipe Arrate} and {R. Chellappa}},
year = 2016,
month = {11},
booktitle = {Computer Vision and Image Understanding},
url = {https://www.semanticscholar.org/paper/da1cc72354f70a187d46664c2318c58d8183c379},
}

Ankan Bansal, Anirudh Nanduri, C. Castillo, Rajeev Ranjan, and R. Chellappa, “UMDFaces: An annotated face dataset for training deep networks,” in 2017 IEEE International Joint Conference on Biometrics (IJCB), 2016.
[BibTeX] [Link]

@inproceedings{66176,
title = {UMDFaces: An annotated face dataset for training deep networks},
author = {{Ankan Bansal} and {Anirudh Nanduri} and {C. Castillo} and {Rajeev Ranjan} and {R. Chellappa}},
year = 2016,
month = {11},
booktitle = {2017 IEEE International Joint Conference on Biometrics (IJCB)},
url = {https://www.semanticscholar.org/paper/ca45746d158e9d58bdb8a62b6d10163a23cf5b6f},
}

Xiantong Zhen, Ling Shao, S. Maybank, and R. Chellappa, “Handcrafted vs. learned representations for human action recognition,” in Image and Vision Computing, 2016.
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@inproceedings{4314532,
title = {Handcrafted vs. learned representations for human action recognition},
author = {{Xiantong Zhen} and {Ling Shao} and {S. Maybank} and {R. Chellappa}},
year = 2016,
month = {11},
booktitle = {Image and Vision Computing},
url = {https://www.semanticscholar.org/paper/d5d55ad2848d908d3b237860327f3a2a19b53b75},
}

T. Wolfe, M. Dredze, and B. Van Durme, “A Study of Imitation Learning Methods for Semantic Role Labeling,” in Proceedings of the Workshop on Structured Prediction for NLP, Austin, TX, 2016, p. 44–53. doi:10.18653/v1/W16-5905
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@inproceedings{wolfe-etal-2016-study,
title = "A Study of Imitation Learning Methods for Semantic Role Labeling",
author = "Wolfe, Travis and
Dredze, Mark and
Van Durme, Benjamin",
editor = "Chang, Kai-Wei and
Chang, Ming-Wei and
Rush, Alexander and
Srikumar, Vivek",
booktitle = "Proceedings of the Workshop on Structured Prediction for {NLP}",
month = nov,
year = "2016",
address = "Austin, TX",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W16-5905",
doi = "10.18653/v1/W16-5905",
pages = "44--53",
}

M. Dredze, N. Andrews, and J. DeYoung, “Twitter at the Grammys: A Social Media Corpus for Entity Linking and Disambiguation,” in Proceedings of the Fourth International Workshop on Natural Language Processing for Social Media, Austin, TX, USA, 2016, p. 20–25. doi:10.18653/v1/W16-6204
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@inproceedings{dredze-etal-2016-twitter,
title = "{T}witter at the Grammys: A Social Media Corpus for Entity Linking and Disambiguation",
author = "Dredze, Mark and
Andrews, Nicholas and
DeYoung, Jay",
editor = "Ku, Lun-Wei and
Hsu, Jane Yung-jen and
Li, Cheng-Te",
booktitle = "Proceedings of the Fourth International Workshop on Natural Language Processing for Social Media",
month = nov,
year = "2016",
address = "Austin, TX, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W16-6204",
doi = "10.18653/v1/W16-6204",
pages = "20--25",
}

Hiroki Ouchi, Kevin Duh, Hiroyuki Shindo, and Yuji Matsumoto, “Transition-Based Dependency Parsing Exploiting Supertags,” in IEEE/ACM Transactions on Audio Speech and Language Processing, 2016.
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@inproceedings{11119843,
title = {Transition-Based Dependency Parsing Exploiting Supertags},
author = {{Hiroki Ouchi} and {Kevin Duh} and {Hiroyuki Shindo} and {Yuji Matsumoto}},
year = 2016,
month = {11},
booktitle = {IEEE/ACM Transactions on Audio Speech and Language Processing},
url = {https://www.semanticscholar.org/paper/72a927349c85f8786630fc28e2f8b9480cc08c51},
}

R. Arora, A. Basu, Poorya Mianjy, and Anirbit Mukherjee, “Understanding Deep Neural Networks with Rectified Linear Units,” in Electron. Colloquium Comput. Complex., 2016.
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@inproceedings{3482308,
title = {Understanding Deep Neural Networks with Rectified Linear Units},
author = {{R. Arora} and {A. Basu} and {Poorya Mianjy} and {Anirbit Mukherjee}},
year = 2016,
month = {11},
booktitle = {Electron. Colloquium Comput. Complex.},
url = {https://www.semanticscholar.org/paper/9375729d21a344a5ccccd5f53556ddf90b957cd9},
}

Rajeev Ranjan, S. Sankaranarayanan, C. Castillo, and R. Chellappa, “An All-In-One Convolutional Neural Network for Face Analysis,” in IEEE International Conference on Automatic Face & Gesture Recognition, 2016.
[BibTeX] [Link]

@inproceedings{5896299,
title = {An All-In-One Convolutional Neural Network for Face Analysis},
author = {{Rajeev Ranjan} and {S. Sankaranarayanan} and {C. Castillo} and {R. Chellappa}},
year = 2016,
month = {11},
booktitle = {IEEE International Conference on Automatic Face & Gesture Recognition},
url = {https://www.semanticscholar.org/paper/93420d9212dd15b3ef37f566e4d57e76bb2fab2f},
}

M. Francis-Landau, B. Xue, J. Eisner, and V. Sarkar, “Fine-grained parallelism in probabilistic parsing with Habanero Java,” in Proceedings of the Sixth Workshop on Irregular Applications: Architectures and Algorithms (IA$^3$), Salt Lake City, 2016, p. 78–81. doi:10.1109/IA3.2016.020
[BibTeX] [Link]

@InProceedings{francislandau-et-al-2016,
doi = "10.1109/IA3.2016.020",
author = "Matthew Francis-Landau and Bing Xue and Jason Eisner
and Vivek Sarkar",
title = "Fine-grained parallelism in probabilistic parsing with
{H}abanero {J}ava",
booktitle = "Proceedings of the Sixth Workshop on Irregular
Applications: Architectures and Algorithms (IA$^3$)",
pages = "78--81",
year = "2016",
month = nov,
address = "Salt Lake City",
publisher = "IEEE Press",
ISBN = "978-1-5090-3867-1",
URL = "http://cs.jhu.edu/~jason/papers/#francislandau-et-al-2016",
}

J. Eisner, “Inside-Outside and Forward-Backward Algorithms are Just Backprop,” in Proceedings of the EMNLP Workshop on Structured Prediction for NLP, Austin, TX, 2016, p. 1–17. doi:10.18653/v1/W16-5901
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@InProceedings{eisner-2016,
aclid = "W16-5901",
doi = "10.18653/v1/W16-5901",
author = "Jason Eisner",
title = "Inside-Outside and Forward-Backward Algorithms are
Just Backprop",
booktitle = "Proceedings of the EMNLP Workshop on Structured
Prediction for NLP",
pages = "1--17",
year = "2016",
month = nov,
address = "Austin, TX",
URL = "http://cs.jhu.edu/~jason/papers/#eisner-2016",
}

T. Vieira, R. Cotterell, and J. Eisner, “Speed-Accuracy Tradeoffs in Tagging with Variable-Order CRFs and Structured Sparsity,” in Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Austin, TX, 2016, p. 1973–1978. doi:10.18653/v1/D16-1206
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@InProceedings{vieira-cotterell-eisner-2016,
aclid = "D16-1206",
doi = "10.18653/v1/D16-1206",
author = "Tim Vieira and Ryan Cotterell and Jason Eisner",
title = "Speed-Accuracy Tradeoffs in Tagging with
Variable-Order {CRF}s and Structured Sparsity",
booktitle = "Proceedings of the Conference on Empirical Methods in
Natural Language Processing (EMNLP)",
pages = "1973--1978",
year = "2016",
month = nov,
address = "Austin, TX",
URL = "http://cs.jhu.edu/~jason/papers/#vieira-cotterell-eisner-2016",
}

Adrian Benton, Braden Hancock, Glen A. Coppersmith, J. Ayers, and Mark Dredze, “After Sandy Hook Elementary: A Year in the Gun Control Debate on Twitter,” in arXiv.org, 2016.
[BibTeX] [Link]

@inproceedings{16893864,
title = {After Sandy Hook Elementary: A Year in the Gun Control Debate on Twitter},
author = {{Adrian Benton} and {Braden Hancock} and {Glen A. Coppersmith} and {J. Ayers} and {Mark Dredze}},
year = 2016,
month = {10},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/0f19e11fb7190e4bc87a6e88529e3ee01831a2e3},
}

X. Wu, K. Duh, and Y. Matsumoto, “A Generalized Framework for Hierarchical Word Sequence Language Model,” in Proceedings of the 30th Pacific Asia Conference on Language, Information and Computation: Oral Papers, Seoul, South Korea, 2016, p. 69–75.
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@inproceedings{wu-etal-2016-generalized,
title = "A Generalized Framework for Hierarchical Word Sequence Language Model",
author = "Wu, Xiaoyi and
Duh, Kevin and
Matsumoto, Yuji",
booktitle = "Proceedings of the 30th Pacific Asia Conference on Language, Information and Computation: Oral Papers",
month = oct,
year = "2016",
address = "Seoul, South Korea",
url = "https://aclanthology.org/Y16-2004",
pages = "69--75",
}

U. Mahbub and R. Chellappa, “PATH: Person authentication using trace histories,” in Ubiquitous Computing, Electronics & Mobile Communication Conference, 2016.
[BibTeX] [Link]

@inproceedings{15820106,
title = {PATH: Person authentication using trace histories},
author = {{U. Mahbub} and {R. Chellappa}},
year = 2016,
month = {10},
booktitle = {Ubiquitous Computing, Electronics & Mobile Communication Conference},
url = {https://www.semanticscholar.org/paper/25c1026057647027b4b633995d54b753e62e40bf},
}

A. Benton, R. Arora, and M. Dredze, “Learning Multiview Embeddings of Twitter Users,” in Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), Berlin, Germany, 2016, p. 14–19. doi:10.18653/v1/P16-2003
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@inproceedings{benton-etal-2016-learning,
title = "Learning Multiview Embeddings of {T}witter Users",
author = "Benton, Adrian and
Arora, Raman and
Dredze, Mark",
editor = "Erk, Katrin and
Smith, Noah A.",
booktitle = "Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)",
month = aug,
year = "2016",
address = "Berlin, Germany",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P16-2003",
doi = "10.18653/v1/P16-2003",
pages = "14--19",
}

F. Yung, K. Duh, T. Komura, and Y. Matsumoto, “Modelling the Usage of Discourse Connectives as Rational Speech Acts,” in Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning, Berlin, Germany, 2016, p. 302–313. doi:10.18653/v1/K16-1030
[BibTeX] [Link]

@inproceedings{yung-etal-2016-modelling,
title = "Modelling the Usage of Discourse Connectives as Rational Speech Acts",
author = "Yung, Frances and
Duh, Kevin and
Komura, Taku and
Matsumoto, Yuji",
editor = "Riezler, Stefan and
Goldberg, Yoav",
booktitle = "Proceedings of the 20th {SIGNLL} Conference on Computational Natural Language Learning",
month = aug,
year = "2016",
address = "Berlin, Germany",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/K16-1030",
doi = "10.18653/v1/K16-1030",
pages = "302--313",
}

S. Ding, K. Duh, H. Khayrallah, P. Koehn, and M. Post, “The JHU Machine Translation Systems for WMT 2016,” in Proceedings of the First Conference on Machine Translation: Volume 2, Shared Task Papers, Berlin, Germany, 2016, p. 272–280. doi:10.18653/v1/W16-2310
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@inproceedings{ding-etal-2016-jhu,
title = "The {JHU} Machine Translation Systems for {WMT} 2016",
author = "Ding, Shuoyang and
Duh, Kevin and
Khayrallah, Huda and
Koehn, Philipp and
Post, Matt",
editor = {Bojar, Ond{\v{r}}ej and
Buck, Christian and
Chatterjee, Rajen and
Federmann, Christian and
Guillou, Liane and
Haddow, Barry and
Huck, Matthias and
Yepes, Antonio Jimeno and
N{\'e}v{\'e}ol, Aur{\'e}lie and
Neves, Mariana and
Pecina, Pavel and
Popel, Martin and
Koehn, Philipp and
Monz, Christof and
Negri, Matteo and
Post, Matt and
Specia, Lucia and
Verspoor, Karin and
Tiedemann, J{\"o}rg and
Turchi, Marco},
booktitle = "Proceedings of the First Conference on Machine Translation: Volume 2, Shared Task Papers",
month = aug,
year = "2016",
address = "Berlin, Germany",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W16-2310",
doi = "10.18653/v1/W16-2310",
pages = "272--280",
}

N. Peng and M. Dredze, “Improving Named Entity Recognition for Chinese Social Media with Word Segmentation Representation Learning,” in Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), Berlin, Germany, 2016, p. 149–155. doi:10.18653/v1/P16-2025
[BibTeX] [Link]

@inproceedings{peng-dredze-2016-improving,
title = "Improving Named Entity Recognition for {C}hinese Social Media with Word Segmentation Representation Learning",
author = "Peng, Nanyun and
Dredze, Mark",
editor = "Erk, Katrin and
Smith, Noah A.",
booktitle = "Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)",
month = aug,
year = "2016",
address = "Berlin, Germany",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P16-2025",
doi = "10.18653/v1/P16-2025",
pages = "149--155",
}

R. Cotterell, C. Kirov, John Sylak-Glassman, D. Yarowsky, J. Eisner, and M. Hulden, “The SIGMORPHON 2016 Shared Task–-Morphological Reinflection,” in Proceedings of the 14th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology, Berlin, 2016, p. 10–22. doi:10.18653/v1/W16-2002
[BibTeX] [Link]

@InProceedings{cotterell-et-al-2016-shared,
aclid = "W16-2002",
doi = "10.18653/v1/W16-2002",
author = "Ryan Cotterell and Christo Kirov and John
Sylak-Glassman and David Yarowsky and Jason Eisner and
Mans Hulden",
title = "The {SIGMORPHON 2016} Shared Task---Morphological
Reinflection",
booktitle = "Proceedings of the 14th SIGMORPHON Workshop on
Computational Research in Phonetics, Phonology, and
Morphology",
pages = "10--22",
year = "2016",
month = aug,
address = "Berlin",
note = "Supplementary material (4 pages) also available.",
URL = "http://cs.jhu.edu/~jason/papers/#cotterell-et-al-2016-shared",
}

R. Knowles, A. Renduchintala, Philipp Koehn, and J. Eisner, “Analyzing Learner Understanding of Novel L2 Vocabulary,” in Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning (CoNLL), Berlin, 2016, p. 126–135. doi:10.18653/v1/K16-1013
[BibTeX] [Link]

@InProceedings{knowles-et-al-2016,
aclid = "K16-1013",
doi = "10.18653/v1/K16-1013",
author = "Rebecca Knowles and Adithya Renduchintala and Philipp
Koehn and Jason Eisner",
title = "Analyzing Learner Understanding of Novel {L2}
Vocabulary",
booktitle = "Proceedings of the 20th SIGNLL Conference on
Computational Natural Language Learning (CoNLL)",
pages = "126--135",
year = "2016",
month = aug,
address = "Berlin",
URL = "http://cs.jhu.edu/~jason/papers/#knowles-et-al-2016",
}

A. Renduchintala, R. Knowles, Philipp Koehn, and J. Eisner, “Creating Interactive Macaronic Interfaces for Language Learning,” in Proceedings of ACL-2016 System Demonstrations, Berlin, 2016, p. 133–138. doi:10.18653/v1/P16-4023
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@InProceedings{renduchintala-et-al-2016-acl-macui,
aclid = "P16-4023",
doi = "10.18653/v1/P16-4023",
author = "Adithya Renduchintala and Rebecca Knowles and Philipp
Koehn and Jason Eisner",
title = "Creating Interactive Macaronic Interfaces for Language
Learning",
booktitle = "Proceedings of ACL-2016 System Demonstrations",
pages = "133--138",
year = "2016",
month = aug,
address = "Berlin",
URL = "http://cs.jhu.edu/~jason/papers/#renduchintala-et-al-2016-acl-macui",
}

A. Renduchintala, R. Knowles, Philipp Koehn, and J. Eisner, “User Modeling in Language Learning with Macaronic Texts,” in Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL), Berlin, 2016, p. 1859–1869. doi:10.18653/v1/P16-1175
[BibTeX] [Link]

@InProceedings{renduchintala-et-al-2016-acl-macmodel,
aclid = "P16-1175",
doi = "10.18653/v1/P16-1175",
author = "Adithya Renduchintala and Rebecca Knowles and Philipp
Koehn and Jason Eisner",
title = "User Modeling in Language Learning with Macaronic
Texts",
booktitle = "Proceedings of the 54th Annual Meeting of the
Association for Computational Linguistics (ACL)",
pages = "1859--1869",
year = "2016",
month = aug,
address = "Berlin",
URL = "http://cs.jhu.edu/~jason/papers/#renduchintala-et-al-2016-acl-macmodel",
}

R. Cotterell, H. Schütze, and Jason Eisner, “Morphological Smoothing and Extrapolation of Word Embeddings,” in Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL), Berlin, 2016, p. 1651–1660. doi:10.18653/v1/P16-1156
[BibTeX] [Link]

@InProceedings{cotterell-et-al-2016-acl,
aclid = "P16-1156",
doi = "10.18653/v1/P16-1156",
author = "Ryan Cotterell and Hinrich Sch{\"{u}}tze and Jason
Eisner",
title = "Morphological Smoothing and Extrapolation of Word
Embeddings",
booktitle = "Proceedings of the 54th Annual Meeting of the
Association for Computational Linguistics (ACL)",
pages = "1651--1660",
year = "2016",
month = aug,
address = "Berlin",
note = "Supplementary material (4 pages) also available.",
URL = "http://cs.jhu.edu/~jason/papers/#cotterell-et-al-2016-acl",
}

N. W. Filardo and J. Eisner, “Rigid Tree Automata With Isolation,” in Proceedings of the Fourth International Workshop on Trends in Tree Automata and Tree Transducers (TTATT), Seoul, 2016.
[BibTeX] [Link]

@InProceedings{filardo-eisner-2016-ttatt,
author = "Nathaniel Wesley Filardo and Jason Eisner",
title = "Rigid Tree Automata With Isolation",
booktitle = "Proceedings of the Fourth International Workshop on
Trends in Tree Automata and Tree Transducers (TTATT)",
year = "2016",
month = aug,
address = "Seoul",
note = "7 pages",
URL = "http://cs.jhu.edu/~jason/papers/#filardo-eisner-2016-ttatt",
}

M. Dredze, M. Osborne, and P. Kambadur, “Geolocation for Twitter: Timing Matters,” in Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, San Diego, California, 2016, p. 1064–1069. doi:10.18653/v1/N16-1122
[BibTeX] [Link]

@inproceedings{dredze-etal-2016-geolocation,
title = "Geolocation for {T}witter: Timing Matters",
author = "Dredze, Mark and
Osborne, Miles and
Kambadur, Prabhanjan",
editor = "Knight, Kevin and
Nenkova, Ani and
Rambow, Owen",
booktitle = "Proceedings of the 2016 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies",
month = jun,
year = "2016",
address = "San Diego, California",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N16-1122",
doi = "10.18653/v1/N16-1122",
pages = "1064--1069",
}

M. Yu, M. Dredze, R. Arora, and M. R. Gormley, “Embedding Lexical Features via Low-Rank Tensors,” in Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, San Diego, California, 2016, p. 1019–1029. doi:10.18653/v1/N16-1117
[BibTeX] [Link]

@inproceedings{yu-etal-2016-embedding,
title = "Embedding Lexical Features via Low-Rank Tensors",
author = "Yu, Mo and
Dredze, Mark and
Arora, Raman and
Gormley, Matthew R.",
editor = "Knight, Kevin and
Nenkova, Ani and
Rambow, Owen",
booktitle = "Proceedings of the 2016 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies",
month = jun,
year = "2016",
address = "San Diego, California",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N16-1117",
doi = "10.18653/v1/N16-1117",
pages = "1019--1029",
}

N. Gao, M. Dredze, and D. Oard, “Knowledge Base Population for Organization Mentions in Email,” in Proceedings of the 5th Workshop on Automated Knowledge Base Construction, San Diego, CA, 2016, p. 24–28. doi:10.18653/v1/W16-1305
[BibTeX] [Link]

@inproceedings{gao-etal-2016-knowledge,
title = "Knowledge Base Population for Organization Mentions in Email",
author = "Gao, Ning and
Dredze, Mark and
Oard, Douglas",
editor = "Pujara, Jay and
Rocktaschel, Tim and
Chen, Danqi and
Singh, Sameer",
booktitle = "Proceedings of the 5th Workshop on Automated Knowledge Base Construction",
month = jun,
year = "2016",
address = "San Diego, CA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W16-1305",
doi = "10.18653/v1/W16-1305",
pages = "24--28",
}

P. Rastogi, R. Cotterell, and Jason Eisner, “Weighting Finite-State Transductions With Neural Context,” in Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT), San Diego, 2016, p. 623–633. doi:10.18653/v1/N16-1076
[BibTeX] [Link]

@InProceedings{rastogi-cotterell-eisner-2016,
aclid = "N16-1076",
doi = "10.18653/v1/N16-1076",
author = "Pushpendre Rastogi and Ryan Cotterell and Jason
Eisner",
title = "Weighting Finite-State Transductions With Neural
Context",
booktitle = "Proceedings of the 2016 Conference of the North
American Chapter of the Association for Computational
Linguistics: Human Language Technologies (NAACL-HLT)",
pages = "623--633",
note = "11 pages. Supplementary material (1 page) also
available",
year = "2016",
month = jun,
address = "San Diego",
URL = "http://cs.jhu.edu/~jason/papers/#rastogi-cotterell-eisner-2016",
}

J. Ayers, J. Westmaas, E. Leas, Adrian Benton, Yunqi Chen, Mark Dredze, and B. Althouse, “Leveraging Big Data to Improve Health Awareness Campaigns: A Novel Evaluation of the Great American Smokeout,” in JMIR Public Health and Surveillance, 2016.
[BibTeX] [Link]

@inproceedings{15593033,
title = {Leveraging Big Data to Improve Health Awareness Campaigns: A Novel Evaluation of the Great American Smokeout},
author = {{J. Ayers} and {J. Westmaas} and {E. Leas} and {Adrian Benton} and {Yunqi Chen} and {Mark Dredze} and {B. Althouse}},
year = 2016,
month = {3},
booktitle = {JMIR Public Health and Surveillance},
url = {https://www.semanticscholar.org/paper/e3cf3a20f6401dfc2b381ac0958af5985aff9cee},
}

Nanyun Peng and Mark Dredze, “Learning Word Segmentation Representations to Improve Named Entity Recognition for Chinese Social Media,” in arXiv.org, 2016.
[BibTeX] [Link]

@inproceedings{8951945,
title = {Learning Word Segmentation Representations to Improve Named Entity Recognition for Chinese Social Media},
author = {{Nanyun Peng} and {Mark Dredze}},
year = 2016,
month = {3},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/7774807438f36c62d34a627e2531a2e69dfb680e},
}

Atul Nakhasi, Sarah G. Bell, R. Passarella, Michael J. Paul, Mark Dredze, and P. Pronovost, “The Potential of Twitter as a Data Source for Patient Safety,” in Journal of patient safety, 2016.
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@inproceedings{15393598,
title = {The Potential of Twitter as a Data Source for Patient Safety},
author = {{Atul Nakhasi} and {Sarah G. Bell} and {R. Passarella} and {Michael J. Paul} and {Mark Dredze} and {P. Pronovost}},
year = 2016,
month = {1},
booktitle = {Journal of patient safety},
url = {https://www.semanticscholar.org/paper/ab80430dd27c64bdb91382b7a0d1aa054364e56b},
}

D. Reynolds, Elizabeth C Godoy, Fred Richardson, E. Singer, D. Sturim, P. Torres-Carrasquillo, N. Dehak, and Stephen Shum, “MITLL 2015 Language Recognition Evaluation System Description.” 2016.
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@inproceedings{64915808,
title = {MITLL 2015 Language Recognition Evaluation System Description},
author = {{D. Reynolds} and {Elizabeth C Godoy} and {Fred Richardson} and {E. Singer} and {D. Sturim} and {P. Torres-Carrasquillo} and {N. Dehak} and {Stephen Shum}},
year = 2016,
month = {1},
booktitle = {},
url = {https://www.semanticscholar.org/paper/00acb0b09637095b5ad96d566cf2688f1afc327c},
}

Michael J. Paul, M. Chisolm, Matthew W. Johnson, R. Vandrey, and Mark Dredze, “Assessing the Validity of Online Drug Forums as a Source for Estimating Demographic and Temporal Trends in Drug Use,” in Journal of addiction medicine, 2016.
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@inproceedings{11763655,
title = {Assessing the Validity of Online Drug Forums as a Source for Estimating Demographic and Temporal Trends in Drug Use},
author = {{Michael J. Paul} and {M. Chisolm} and {Matthew W. Johnson} and {R. Vandrey} and {Mark Dredze}},
year = 2016,
month = {9},
booktitle = {Journal of addiction medicine},
url = {https://www.semanticscholar.org/paper/3ac0006f318a35be541605769bd767eb00e8af6b},
}

Mark Dredze, David A. Broniatowski, and Karen Hilyard, “Zika vaccine misconceptions: A social media analysis.,” in Vaccine, 2016.
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@inproceedings{21187335,
title = {Zika vaccine misconceptions: A social media analysis.},
author = {{Mark Dredze} and {David A. Broniatowski} and {Karen Hilyard}},
year = 2016,
month = {6},
booktitle = {Vaccine},
url = {https://www.semanticscholar.org/paper/f77c62e36f5e0e86dec14b68e8496aeddeeacae3},
}

Vishal M. Patel, R. Chellappa, Deepak Chandra, and Brandon Barbello, “Continuous User Authentication on Mobile Devices: Recent progress and remaining challenges,” in IEEE Signal Processing Magazine, 2016.
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@inproceedings{14179050,
title = {Continuous User Authentication on Mobile Devices: Recent progress and remaining challenges},
author = {{Vishal M. Patel} and {R. Chellappa} and {Deepak Chandra} and {Brandon Barbello}},
year = 2016,
month = {7},
booktitle = {IEEE Signal Processing Magazine},
url = {https://www.semanticscholar.org/paper/b77c9f03d6300d5d1d193e92c0ac422bf3b586c6},
}

Daniel R. Mendat, S. Chin, S. Furber, and A. Andreou, “Neuromorphic sampling on the SpiNNaker and parallella chip multiprocessors,” in 2016 IEEE 7th Latin American Symposium on Circuits & Systems (LASCAS), 2016.
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@inproceedings{39457366,
title = {Neuromorphic sampling on the SpiNNaker and parallella chip multiprocessors},
author = {{Daniel R. Mendat} and {S. Chin} and {S. Furber} and {A. Andreou}},
year = 2016,
month = {4},
booktitle = {2016 IEEE 7th Latin American Symposium on Circuits & Systems (LASCAS)},
url = {https://www.semanticscholar.org/paper/39122073e998bf4ef5617097e5082557351d1ac7},
}

M. Biggerstaff, David Alper, Mark Dredze, S. Fox, I. C. Fung, K. Hickmann, B. Lewis, Roni Rosenfeld, J. Shaman, Ming-Hsiang Tsou, P. Velardi, Alessandro Vespignani, and L. Finelli, “Results from the centers for disease control and prevention’s predict the 2013–2014 Influenza Season Challenge,” in BMC Infectious Diseases, 2016.
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@inproceedings{2850015,
title = {Results from the centers for disease control and prevention’s predict the 2013–2014 Influenza Season Challenge},
author = {{M. Biggerstaff} and {David Alper} and {Mark Dredze} and {S. Fox} and {I. C. Fung} and {K. Hickmann} and {B. Lewis} and {Roni Rosenfeld} and {J. Shaman} and {Ming-Hsiang Tsou} and {P. Velardi} and {Alessandro Vespignani} and {L. Finelli}},
year = 2016,
month = {7},
booktitle = {BMC Infectious Diseases},
url = {https://www.semanticscholar.org/paper/c490ccb194330ad3d6d661339f0ab1c1cde8a13d},
}

Mark Dredze, P. Kambadur, Gary Kazantsev, Gideon Mann, and M. Osborne, “How Twitter is Changing the Nature of Financial News Discovery,” in DSMM@SIGMOD, 2016.
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@inproceedings{1286563,
title = {How Twitter is Changing the Nature of Financial News Discovery},
author = {{Mark Dredze} and {P. Kambadur} and {Gary Kazantsev} and {Gideon Mann} and {M. Osborne}},
year = 2016,
month = {6},
booktitle = {DSMM@SIGMOD},
url = {https://www.semanticscholar.org/paper/2b5d7d3baef51c66cce0f8dc4807d7b88bcb9239},
}

Jingjing Zheng, Zhuolin Jiang, and R. Chellappa, “Submodular Attribute Selection for Visual Recognition.,” in IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016.
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@inproceedings{39151366,
title = {Submodular Attribute Selection for Visual Recognition.},
author = {{Jingjing Zheng} and {Zhuolin Jiang} and {R. Chellappa}},
year = 2016,
booktitle = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
url = {https://www.semanticscholar.org/paper/6c399614f2073a321d70887082b2f41f131cb686},
}

Emily M. Hand and R. Chellappa, “Attributes for Improved Attributes: A Multi-Task Network for Attribute Classification,” in arXiv.org, 2016.
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@inproceedings{8558854,
title = {Attributes for Improved Attributes: A Multi-Task Network for Attribute Classification},
author = {{Emily M. Hand} and {R. Chellappa}},
year = 2016,
month = {4},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/87147418f863e3d8ff8c97db0b42695a1c28195b},
}

Frances Yung, Kevin Duh, T. Komura, and Yuji Matsumoto, “Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning, CoNLL 2016, Berlin, Germany, August 11-12, 2016,” in Conference on Computational Natural Language Learning, 2016.
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@inproceedings{13640716,
title = {Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning, CoNLL 2016, Berlin, Germany, August 11-12, 2016},
author = {{Frances Yung} and {Kevin Duh} and {T. Komura} and {Yuji Matsumoto}},
year = 2016,
booktitle = {Conference on Computational Natural Language Learning},
url = {https://www.semanticscholar.org/paper/3c618089f5da30f1e06222c4799f89b1292ea4de},
}

Jun-Cheng Chen, Amit Kumar, Rajeev Ranjan, Vishal M. Patel, A. Alavi, and R. Chellappa, “A cascaded convolutional neural network for age estimation of unconstrained faces,” in 2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS), 2016.
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@inproceedings{16523471,
title = {A cascaded convolutional neural network for age estimation of unconstrained faces},
author = {{Jun-Cheng Chen} and {Amit Kumar} and {Rajeev Ranjan} and {Vishal M. Patel} and {A. Alavi} and {R. Chellappa}},
year = 2016,
month = {9},
booktitle = {2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS)},
url = {https://www.semanticscholar.org/paper/d00e9a6339e34c613053d3b2c132fccbde547b56},
}

Deyi Xiong, Kevin Duh, Eneko Agirre, Nora Aranberri, and Houfeng Wang, “Proceedings of the 2nd Workshop on Semantics-Driven Machine Translation (SedMT 2016).” 2016.
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@inproceedings{64838888,
title = {Proceedings of the 2nd Workshop on Semantics-Driven Machine Translation (SedMT 2016)},
author = {{Deyi Xiong} and {Kevin Duh} and {Eneko Agirre} and {Nora Aranberri} and {Houfeng Wang}},
year = 2016,
booktitle = {},
url = {https://www.semanticscholar.org/paper/296e929a7c3faa6d8942d147941af413b7fec7d8},
}

A. Andreou, Tomas Figliolia, Kayode A. Sanni, Thomas S. Murray, Gaspar Tognetti, Daniel R. Mendat, J. Molin, M. Villemur, P. Pouliquen, P. Julián, R. Etienne-Cummings, and I. Doxas, “Bio-inspired system architecture for energy efficient, BIGDATA computing with application to wide area motion imagery,” in 2016 IEEE 7th Latin American Symposium on Circuits & Systems (LASCAS), 2016.
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@inproceedings{23235443,
title = {Bio-inspired system architecture for energy efficient, BIGDATA computing with application to wide area motion imagery},
author = {{A. Andreou} and {Tomas Figliolia} and {Kayode A. Sanni} and {Thomas S. Murray} and {Gaspar Tognetti} and {Daniel R. Mendat} and {J. Molin} and {M. Villemur} and {P. Pouliquen} and {P. Julián} and {R. Etienne-Cummings} and {I. Doxas}},
year = 2016,
month = {4},
booktitle = {2016 IEEE 7th Latin American Symposium on Circuits & Systems (LASCAS)},
url = {https://www.semanticscholar.org/paper/e2d89cf69fb612e42b381cf9b8f24270f377de3a},
}

B. Bushman, K. Newman, Sandra L. Calvert, G. Downey, Mark Dredze, Michael R. Gottfredson, N. Jablonski, A. Masten, C. Morrill, Dan Neill, D. Romer, and D. Webster, “Youth violence: What we know and what we need to know.,” in American Psychologist, 2016.
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@inproceedings{25746868,
title = {Youth violence: What we know and what we need to know.},
author = {{B. Bushman} and {K. Newman} and {Sandra L. Calvert} and {G. Downey} and {Mark Dredze} and {Michael R. Gottfredson} and {N. Jablonski} and {A. Masten} and {C. Morrill} and {Dan Neill} and {D. Romer} and {D. Webster}},
year = 2016,
booktitle = {American Psychologist},
url = {https://www.semanticscholar.org/paper/8406e074b237e9f36cb026f243e261d528a06f7c},
}

U. Pal, Cheng-lin Liu, R. Chellappa, K. Kise, Liang Wang, Paolo Remagnino, H. Byun, R. Parameswaran, and Chee Seng Chan, “Welcome message from the chair.” 2016.
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@inproceedings{189031063,
title = {Welcome message from the chair},
author = {{U. Pal} and {Cheng-lin Liu} and {R. Chellappa} and {K. Kise} and {Liang Wang} and {Paolo Remagnino} and {H. Byun} and {R. Parameswaran} and {Chee Seng Chan}},
year = 2016,
month = {6},
booktitle = {},
url = {https://www.semanticscholar.org/paper/a07f982eba12eb631df0e6f9436b7e8fbbd9bcc6},
}

Kaustav Nandy, R. Chellappa, Amit Kumar, and S. Lockett, “Segmentation of Nuclei From 3D Microscopy Images of Tissue via Graphcut Optimization,” in IEEE Journal on Selected Topics in Signal Processing, 2016.
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@inproceedings{17963009,
title = {Segmentation of Nuclei From 3D Microscopy Images of Tissue via Graphcut Optimization},
author = {{Kaustav Nandy} and {R. Chellappa} and {Amit Kumar} and {S. Lockett}},
year = 2016,
month = {2},
booktitle = {IEEE Journal on Selected Topics in Signal Processing},
url = {https://www.semanticscholar.org/paper/bf37c1464995b457c5ff8b2d825a102fccef1d95},
}

Frances Yung, Kevin Duh, T. Komura, and Yuji Matsumoto, “Modeling the Interpretation of Discourse Connectives.” 2016.
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@inproceedings{63659974,
title = {Modeling the Interpretation of Discourse Connectives},
author = {{Frances Yung} and {Kevin Duh} and {T. Komura} and {Yuji Matsumoto}},
year = 2016,
booktitle = {},
url = {https://www.semanticscholar.org/paper/f0f57c381bc0ef1e06f956f2f732e93617784331},
}

A. Kuncoro, Yu Sawai, Kevin Duh, and Yuji Matsumoto, “Dependency Parsing with LSTMs: An Empirical Evaluation,” in arXiv.org, 2016.
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@inproceedings{735949,
title = {Dependency Parsing with LSTMs: An Empirical Evaluation},
author = {{A. Kuncoro} and {Yu Sawai} and {Kevin Duh} and {Yuji Matsumoto}},
year = 2016,
month = {4},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/8ce0023611d4d5f0e9654a289e165f600216c76d},
}

H. Korth, K. Strohbehn, Francisco Tejada, A. Andreou, J. Kitching, S. Knappe, S. Lehtonen, S. London, and Matiwos Kafel, “Miniature atomic scalar magnetometer for space based on the rubidium isotope 87Rb,” in Journal of Geophysical Research – Space Physics, 2016.
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@inproceedings{21973775,
title = {Miniature atomic scalar magnetometer for space based on the rubidium isotope 87Rb},
author = {{H. Korth} and {K. Strohbehn} and {Francisco Tejada} and {A. Andreou} and {J. Kitching} and {S. Knappe} and {S. Lehtonen} and {S. London} and {Matiwos Kafel}},
year = 2016,
month = {8},
booktitle = {Journal of Geophysical Research - Space Physics},
url = {https://www.semanticscholar.org/paper/bf133147b39969efa2aaf14727be8f426bf6289f},
}

Mohammed E. Fathy, A. Alavi, and R. Chellappa, “Discriminative Log-Euclidean Feature Learning for Sparse Representation-Based Recognition of Faces from Videos,” in International Joint Conference on Artificial Intelligence, 2016.
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@inproceedings{12364145,
title = {Discriminative Log-Euclidean Feature Learning for Sparse Representation-Based Recognition of Faces from Videos},
author = {{Mohammed E. Fathy} and {A. Alavi} and {R. Chellappa}},
year = 2016,
month = {7},
booktitle = {International Joint Conference on Artificial Intelligence},
url = {https://www.semanticscholar.org/paper/970c0d6c0fd2ebe7c5921a45bc70f6345c844ff3},
}

Animesh Koratana, Mark Dredze, M. Chisolm, Matthew W. Johnson, and Michael J. Paul, “Studying Anonymous Health Issues and Substance Use on College Campuses with Yik Yak,” in AAAI Workshop: WWW and Population Health Intelligence, 2016.
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@inproceedings{7015943,
title = {Studying Anonymous Health Issues and Substance Use on College Campuses with Yik Yak},
author = {{Animesh Koratana} and {Mark Dredze} and {M. Chisolm} and {Matthew W. Johnson} and {Michael J. Paul}},
year = 2016,
month = {3},
booktitle = {AAAI Workshop: WWW and Population Health Intelligence},
url = {https://www.semanticscholar.org/paper/bd4cb7d25157f67e2d6f1e60b6c9e75655289ae3},
}

Hongyu Xu, Jingjing Zheng, A. Alavi, and R. Chellappa, “Learning a structured dictionary for video-based face recognition,” in IEEE Workshop/Winter Conference on Applications of Computer Vision, 2016.
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@inproceedings{19029552,
title = {Learning a structured dictionary for video-based face recognition},
author = {{Hongyu Xu} and {Jingjing Zheng} and {A. Alavi} and {R. Chellappa}},
year = 2016,
month = {3},
booktitle = {IEEE Workshop/Winter Conference on Applications of Computer Vision},
url = {https://www.semanticscholar.org/paper/945ef646679b6c575d3bbef9c6fc0a9629ac1b62},
}

Xingguo Li, T. Zhao, R. Arora, Han Liu, and Mingyi Hong, “On Faster Convergence of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization,” in Journal of machine learning research, 2016.
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@inproceedings{16665228,
title = {On Faster Convergence of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization},
author = {{Xingguo Li} and {T. Zhao} and {R. Arora} and {Han Liu} and {Mingyi Hong}},
year = 2016,
month = {7},
booktitle = {Journal of machine learning research},
url = {https://www.semanticscholar.org/paper/486956c45fa19b2d0d794501ec296f607ed1eeb5},
}

Jun-Cheng Chen, Rajeev Ranjan, S. Sankaranarayanan, Amit Kumar, Ching-Hui Chen, Vishal M. Patel, C. Castillo, and R. Chellappa, “Unconstrained Still/Video-Based Face Verification with Deep Convolutional Neural Networks,” in International Journal of Computer Vision, 2016.
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@inproceedings{3442236,
title = {Unconstrained Still/Video-Based Face Verification with Deep Convolutional Neural Networks},
author = {{Jun-Cheng Chen} and {Rajeev Ranjan} and {S. Sankaranarayanan} and {Amit Kumar} and {Ching-Hui Chen} and {Vishal M. Patel} and {C. Castillo} and {R. Chellappa}},
year = 2016,
month = {5},
booktitle = {International Journal of Computer Vision},
url = {https://www.semanticscholar.org/paper/3d78c144672c4ee76d92d21dad012bdf3c3aa1a0},
}

Xingguo Li, T. Zhao, R. Arora, Han Liu, and Jarvis D. Haupt, “Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning,” in International Conference on Machine Learning, 2016.
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@inproceedings{5007028,
title = {Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning},
author = {{Xingguo Li} and {T. Zhao} and {R. Arora} and {Han Liu} and {Jarvis D. Haupt}},
year = 2016,
month = {5},
booktitle = {International Conference on Machine Learning},
url = {https://www.semanticscholar.org/paper/e61ca3bf0331722c05478b61eb4b7ab3a86854b1},
}

L. Davis, R. Chellappa, Derek Hoiem, A. Gupta, M. Hebert, E. Aminoff, HyunSoo Park, D. Forsyth, Jianbo Shi, and M. Tarr, “Rich Representations with Exposed Semantics for Deep Visual Reasoning.” 2016.
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@inproceedings{195947975,
title = {Rich Representations with Exposed Semantics for Deep Visual Reasoning},
author = {{L. Davis} and {R. Chellappa} and {Derek Hoiem} and {A. Gupta} and {M. Hebert} and {E. Aminoff} and {HyunSoo Park} and {D. Forsyth} and {Jianbo Shi} and {M. Tarr}},
year = 2016,
month = {6},
booktitle = {},
url = {https://www.semanticscholar.org/paper/a4b74383c3946aabba06641bd531bcb54301eac7},
}

S. Sankaranarayanan, A. Alavi, and R. Chellappa, “Triplet Similarity Embedding for Face Verification,” in arXiv.org, 2016.
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@inproceedings{2450630,
title = {Triplet Similarity Embedding for Face Verification},
author = {{S. Sankaranarayanan} and {A. Alavi} and {R. Chellappa}},
year = 2016,
month = {2},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/729f9ef5dad29eadae16f33682b48c4806af2029},
}

Jingjing Zheng, Zhuolin Jiang, and R. Chellappa, “Cross-view Action Recognition via Transferable Dictionary Learning.,” in IEEE Transactions on Image Processing, 2016.
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@inproceedings{195674402,
title = {Cross-view Action Recognition via Transferable Dictionary Learning.},
author = {{Jingjing Zheng} and {Zhuolin Jiang} and {R. Chellappa}},
year = 2016,
booktitle = {IEEE Transactions on Image Processing},
url = {https://www.semanticscholar.org/paper/a7eaaaafb923f9aaf723c0276a462d7cbe93fd9a},
}

S. Zafeiriou, Guoying Zhao, M. Pietikäinen, R. Chellappa, I. Kotsia, and J. Cohn, “Editorial of special issue on spontaneous facial behaviour analysis,” in Computer Vision and Image Understanding, 2016.
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@inproceedings{34326373,
title = {Editorial of special issue on spontaneous facial behaviour analysis},
author = {{S. Zafeiriou} and {Guoying Zhao} and {M. Pietikäinen} and {R. Chellappa} and {I. Kotsia} and {J. Cohn}},
year = 2016,
month = {6},
booktitle = {Computer Vision and Image Understanding},
url = {https://www.semanticscholar.org/paper/1a8581254806ce591ea3f38760acec71c63e4e67},
}

Jian Su, Kevin Duh, and X. Carreras, “Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing,” in Conference on Empirical Methods in Natural Language Processing, 2016.
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@inproceedings{88500266,
title = {Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing},
author = {{Jian Su} and {Kevin Duh} and {X. Carreras}},
year = 2016,
booktitle = {Conference on Empirical Methods in Natural Language Processing},
url = {https://www.semanticscholar.org/paper/b982ab51b2ef52d1a19ec69da4e6d4ef52ee10da},
}

R. Knowles, Mark Dredze, K. Evans, E. Lasser, Tom M. Richards, J. Weiner, and Hadi Kharrazi, “High Risk Pregnancy Prediction from Clinical Text.” 2016.
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@inproceedings{18483986,
title = {High Risk Pregnancy Prediction from Clinical Text},
author = {{R. Knowles} and {Mark Dredze} and {K. Evans} and {E. Lasser} and {Tom M. Richards} and {J. Weiner} and {Hadi Kharrazi}},
year = 2016,
booktitle = {},
url = {https://www.semanticscholar.org/paper/6a4e4db4ca3df11b6094007fe614d5af86efc01c},
}

Masashi Tsubaki, Kevin Duh, M. Shimbo, and Yuji Matsumoto, “Non-Linear Similarity Learning for Compositionality,” in AAAI Conference on Artificial Intelligence, 2016.
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@inproceedings{34772205,
title = {Non-Linear Similarity Learning for Compositionality},
author = {{Masashi Tsubaki} and {Kevin Duh} and {M. Shimbo} and {Yuji Matsumoto}},
year = 2016,
month = {2},
booktitle = {AAAI Conference on Artificial Intelligence},
url = {https://www.semanticscholar.org/paper/3d6f95fa4e1771d13f4a523063b244e2328f1aa0},
}

Neeraja Nagarajan, B. Smart, A. Nastasi, Z. J. Effendi, S. Murali, Z. Berger, Eric B. Schneider, Mark Dredze, and J. Canner, “An analysis of twitter conversations on global surgical care,” in Annals of global health, 2016.
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@inproceedings{168229093,
title = {An analysis of twitter conversations on global surgical care},
author = {{Neeraja Nagarajan} and {B. Smart} and {A. Nastasi} and {Z. J. Effendi} and {S. Murali} and {Z. Berger} and {Eric B. Schneider} and {Mark Dredze} and {J. Canner}},
year = 2016,
month = {5},
booktitle = {Annals of global health},
url = {https://www.semanticscholar.org/paper/68d71e5e4255ee248940023c32b53e7559ffa197},
}

D. A. Shaw and R. Chellappa, “Domain Adaptation Using the Grassmann Manifold.” 2016.
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@inproceedings{124688230,
title = {Domain Adaptation Using the Grassmann Manifold},
author = {{D. A. Shaw} and {R. Chellappa}},
year = 2016,
booktitle = {},
url = {https://www.semanticscholar.org/paper/9d58e0f34b5313219b0444dc87a6f98a79797b6f},
}

Xingguo Li, R. Arora, Han Liu, Jarvis D. Haupt, and Tuo Zhao, “Nonconvex Sparse Learning via Stochastic Optimization with Progressive Variance Reduction,” in arXiv: Learning, 2016.
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@inproceedings{5533498,
title = {Nonconvex Sparse Learning via Stochastic Optimization with Progressive Variance Reduction},
author = {{Xingguo Li} and {R. Arora} and {Han Liu} and {Jarvis D. Haupt} and {Tuo Zhao}},
year = 2016,
month = {5},
booktitle = {arXiv: Learning},
url = {https://www.semanticscholar.org/paper/a4edc4aa0bf3eb9d1d0e9aec8d248d088a96af73},
}

Kota Hara and R. Chellappa, “Growing Regression Tree Forests by Classification for Continuous Object Pose Estimation,” in International Journal of Computer Vision, 2016.
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@inproceedings{255106135,
title = {Growing Regression Tree Forests by Classification for Continuous Object Pose Estimation},
author = {{Kota Hara} and {R. Chellappa}},
year = 2016,
month = {8},
booktitle = {International Journal of Computer Vision},
url = {https://www.semanticscholar.org/paper/f53a72e646e9ee81f88b8b21223cfcfe8a38cefc},
}

Amit Kumar, Rajeev Ranjan, Vishal M. Patel, and R. Chellappa, “Face Alignment by Local Deep Descriptor Regression,” in arXiv.org, 2016.
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@inproceedings{8632772,
title = {Face Alignment by Local Deep Descriptor Regression},
author = {{Amit Kumar} and {Rajeev Ranjan} and {Vishal M. Patel} and {R. Chellappa}},
year = 2016,
month = {1},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/ceeb67bf53ffab1395c36f1141b516f893bada27},
}

A. Alavi, Vishal M. Patel, and R. Chellappa, “Optimized Kernel-based Projection Space of Riemannian Manifolds,” in arXiv: Computer Vision and Pattern Recognition, 2016.
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@inproceedings{16223054,
title = {Optimized Kernel-based Projection Space of Riemannian Manifolds},
author = {{A. Alavi} and {Vishal M. Patel} and {R. Chellappa}},
year = 2016,
month = {2},
booktitle = {arXiv: Computer Vision and Pattern Recognition},
url = {https://www.semanticscholar.org/paper/a05da0eae221ce50f6d742ea8611fbf084e1a557},
}

J. Ayers, B. Althouse, Jon-Patrick Allem, E. Leas, Mark Dredze, and Rebecca S. Williams, “Revisiting the Rise of Electronic Nicotine Delivery Systems Using Search Query Surveillance.,” in American Journal of Preventive Medicine, 2016.
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@inproceedings{8811772,
title = {Revisiting the Rise of Electronic Nicotine Delivery Systems Using Search Query Surveillance.},
author = {{J. Ayers} and {B. Althouse} and {Jon-Patrick Allem} and {E. Leas} and {Mark Dredze} and {Rebecca S. Williams}},
year = 2016,
month = {6},
booktitle = {American Journal of Preventive Medicine},
url = {https://www.semanticscholar.org/paper/4d7480c3c927399c9693838655cac0c5b64cab68},
}

Raviteja Vemulapalli and R. Chellappa, “Rolling Rotations for Recognizing Human Actions from 3D Skeletal Data,” in Computer Vision and Pattern Recognition, 2016.
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@inproceedings{15604798,
title = {Rolling Rotations for Recognizing Human Actions from 3D Skeletal Data},
author = {{Raviteja Vemulapalli} and {R. Chellappa}},
year = 2016,
month = {6},
booktitle = {Computer Vision and Pattern Recognition},
url = {https://www.semanticscholar.org/paper/d632613152d93e4ba4e2978f337de5cc9911ea8c},
}

R. Chellappa, Jun-Cheng Chen, Rajeev Ranjan, S. Sankaranarayanan, Amit Kumar, Vishal M. Patel, and C. Castillo, “Towards the design of an end-to-end automated system for image and video-based recognition,” in Information Theory and Applications Workshop, 2016.
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@inproceedings{9879142,
title = {Towards the design of an end-to-end automated system for image and video-based recognition},
author = {{R. Chellappa} and {Jun-Cheng Chen} and {Rajeev Ranjan} and {S. Sankaranarayanan} and {Amit Kumar} and {Vishal M. Patel} and {C. Castillo}},
year = 2016,
month = {1},
booktitle = {Information Theory and Applications Workshop},
url = {https://www.semanticscholar.org/paper/d29fd8940868b9d41d0cd0b2b89c558046266604},
}

A. Alavi, Vishal M. Patel, and R. Chellappa, “Distance Preserving Projection Space of Symmetric Positive Definite Manifolds,” in arXiv.org, 2016.
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@inproceedings{16724318,
title = {Distance Preserving Projection Space of Symmetric Positive Definite Manifolds},
author = {{A. Alavi} and {Vishal M. Patel} and {R. Chellappa}},
year = 2016,
month = {2},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/7e6b11674e989d6a86afda241a51f7fa3790b93e},
}

B. Riggan, Nathan J. Short, Shuowen Hu, Afsane Ghasemi, Simon Denman, S. Sridharan, C. Fookes, Xiang Yu, Jianchao Yang, Linjie Luo, Wilmot Li, Jonathan Brandt, Dimitris N. Metaxas, David Chan, M. Mahoor, Tejas I. Dhamecha, Praneet Sharma, Richa Singh, Mayank Vatsa, A. Noore, Jun-Cheng Chen, Vishal M. Patel, R. Chellappa, Soumyadip Sengupta, C. Castillo, and D. Jacobs, “2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016, Lake Placid, NY, USA, March 7-10, 2016,” in IEEE Workshop/Winter Conference on Applications of Computer Vision, 2016.
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@inproceedings{42536071,
title = {2016 IEEE Winter Conference on Applications of Computer Vision, WACV 2016, Lake Placid, NY, USA, March 7-10, 2016},
author = {{B. Riggan} and {Nathan J. Short} and {Shuowen Hu} and {Afsane Ghasemi} and {Simon Denman} and {S. Sridharan} and {C. Fookes} and {Xiang Yu} and {Jianchao Yang} and {Linjie Luo} and {Wilmot Li} and {Jonathan Brandt} and {Dimitris N. Metaxas} and {David Chan} and {M. Mahoor} and {Tejas I. Dhamecha} and {Praneet Sharma} and {Richa Singh} and {Mayank Vatsa} and {A. Noore} and {Jun-Cheng Chen} and {Vishal M. Patel} and {R. Chellappa} and {Soumyadip Sengupta} and {C. Castillo} and {D. Jacobs}},
year = 2016,
booktitle = {IEEE Workshop/Winter Conference on Applications of Computer Vision},
url = {https://www.semanticscholar.org/paper/316ffa55aeb011e2ac5e882dd3b6d24ee00e6aec},
}

Mark Dredze, David A. Broniatowski, Michael C. Smith, and Karen Hilyard, “Understanding Vaccine Refusal: Why We Need Social Media Now.,” in American Journal of Preventive Medicine, 2016.
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@inproceedings{8919622,
title = {Understanding Vaccine Refusal: Why We Need Social Media Now.},
author = {{Mark Dredze} and {David A. Broniatowski} and {Michael C. Smith} and {Karen Hilyard}},
year = 2016,
month = {4},
booktitle = {American Journal of Preventive Medicine},
url = {https://www.semanticscholar.org/paper/52810df5339436f0bd5b014846fb6adca89406c4},
}

Nitesh Shroff, Rushil Anirudh, and R. Chellappa, “Summarization and Search Over Geometric Spaces.” 2016.
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@inproceedings{124876232,
title = {Summarization and Search Over Geometric Spaces},
author = {{Nitesh Shroff} and {Rushil Anirudh} and {R. Chellappa}},
year = 2016,
booktitle = {},
url = {https://www.semanticscholar.org/paper/7e55629c938420abf3975e9467fae71d56ca40a4},
}

Kristin N. Hageman, Z. Kalayjian, Francisco Tejada, Bryce Chiang, Mehdi A. Rahman, G. Fridman, C. Dai, P. Pouliquen, Julio Georgiou, C. C. Santina, and A. Andreou, “A CMOS Neural Interface for a Multichannel Vestibular Prosthesis,” in IEEE Transactions on Biomedical Circuits and Systems, 2016.
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@inproceedings{553823,
title = {A CMOS Neural Interface for a Multichannel Vestibular Prosthesis},
author = {{Kristin N. Hageman} and {Z. Kalayjian} and {Francisco Tejada} and {Bryce Chiang} and {Mehdi A. Rahman} and {G. Fridman} and {C. Dai} and {P. Pouliquen} and {Julio Georgiou} and {C. C. Santina} and {A. Andreou}},
year = 2016,
month = {4},
booktitle = {IEEE Transactions on Biomedical Circuits and Systems},
url = {https://www.semanticscholar.org/paper/b285ca24ac25fa86cf35608e65f9d481b75d4d33},
}

Maya Kabkab, A. Alavi, and R. Chellappa, “DCNNs on a Diet: Sampling Strategies for Reducing the Training Set Size,” in arXiv.org, 2016.
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@inproceedings{14620529,
title = {DCNNs on a Diet: Sampling Strategies for Reducing the Training Set Size},
author = {{Maya Kabkab} and {A. Alavi} and {R. Chellappa}},
year = 2016,
month = {6},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/c9bc1b03b50863a24d417501e7e0b1182bb2c900},
}

U. Mahbub, Sayantan Sarkar, Vishal M. Patel, and R. Chellappa, “Active user authentication for smartphones: A challenge data set and benchmark results,” in 2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS), 2016.
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@inproceedings{9349603,
title = {Active user authentication for smartphones: A challenge data set and benchmark results},
author = {{U. Mahbub} and {Sayantan Sarkar} and {Vishal M. Patel} and {R. Chellappa}},
year = 2016,
month = {9},
booktitle = {2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS)},
url = {https://www.semanticscholar.org/paper/02820c1491b10a1ff486fed32c269e4077c36551},
}

M. Choudhury, Emre Kıcıman, Mark Dredze, Glen A. Coppersmith, and Mrinal Kumar, “Discovering Shifts to Suicidal Ideation from Mental Health Content in Social Media,” in International Conference on Human Factors in Computing Systems, 2016.
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@inproceedings{15870680,
title = {Discovering Shifts to Suicidal Ideation from Mental Health Content in Social Media},
author = {{M. Choudhury} and {Emre Kıcıman} and {Mark Dredze} and {Glen A. Coppersmith} and {Mrinal Kumar}},
year = 2016,
month = {5},
booktitle = {International Conference on Human Factors in Computing Systems},
url = {https://www.semanticscholar.org/paper/548f8d0f906f54427e1d6e86802080f500b35a8d},
}

E. Leas, B. Althouse, Mark Dredze, Nick Obradovich, J. Fowler, S. Noar, Jon-Patrick Allem, and J. Ayers, “Big Data Sensors of Organic Advocacy: The Case of Leonardo DiCaprio and Climate Change,” in PLoS ONE, 2016.
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@inproceedings{17653562,
title = {Big Data Sensors of Organic Advocacy: The Case of Leonardo DiCaprio and Climate Change},
author = {{E. Leas} and {B. Althouse} and {Mark Dredze} and {Nick Obradovich} and {J. Fowler} and {S. Noar} and {Jon-Patrick Allem} and {J. Ayers}},
year = 2016,
month = {8},
booktitle = {PLoS ONE},
url = {https://www.semanticscholar.org/paper/d9689675eea9334798e0507b798452519f974364},
}

Jingjing Zheng, Zhuolin Jiang, and R. Chellappa, “Cross-View Action Recognition via Transferable Dictionary Learning,” in IEEE Transactions on Image Processing, 2016.
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@inproceedings{11923955,
title = {Cross-View Action Recognition via Transferable Dictionary Learning},
author = {{Jingjing Zheng} and {Zhuolin Jiang} and {R. Chellappa}},
year = 2016,
month = {6},
booktitle = {IEEE Transactions on Image Processing},
url = {https://www.semanticscholar.org/paper/d5727de9817e2018f0b72677fdd6405d6194bd1f},
}

Ruizhi Li, Sri Harish Reddy Mallidi, L. Burget, Oldrich Plchot, and N. Dehak, “Exploiting Hidden-Layer Responses of Deep Neural Networks for Language Recognition,” in Interspeech, 2016.
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@inproceedings{2879199,
title = {Exploiting Hidden-Layer Responses of Deep Neural Networks for Language Recognition},
author = {{Ruizhi Li} and {Sri Harish Reddy Mallidi} and {L. Burget} and {Oldrich Plchot} and {N. Dehak}},
year = 2016,
month = {9},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/8b96f71e6895b448841d79eaa3836150abea48f9},
}

Sayantan Sarkar, Vishal M. Patel, and R. Chellappa, “Deep feature-based face detection on mobile devices,” in International Conference on Identity, Security and Behavior Analysis, 2016.
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@inproceedings{397520,
title = {Deep feature-based face detection on mobile devices},
author = {{Sayantan Sarkar} and {Vishal M. Patel} and {R. Chellappa}},
year = 2016,
month = {2},
booktitle = {International Conference on Identity, Security and Behavior Analysis},
url = {https://www.semanticscholar.org/paper/4592f5df520842f8406753523d3eee464722d78e},
}

Jingjing Zheng, Zhuolin Jiang, and R. Chellappa, “Cross-View Action Recognition via Transferable Dictionary Learning.,” in IEEE Transactions on Image Processing, 2016.
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@inproceedings{54489677,
title = {Cross-View Action Recognition via Transferable Dictionary Learning.},
author = {{Jingjing Zheng} and {Zhuolin Jiang} and {R. Chellappa}},
year = 2016,
month = {6},
booktitle = {IEEE Transactions on Image Processing},
url = {https://www.semanticscholar.org/paper/79c569d2a8c64aa337d34b1035d6508fdf01d055},
}

Hui Ding, S. Zhou, and R. Chellappa, “FaceNet2ExpNet: Regularizing a Deep Face Recognition Net for Expression Recognition,” in IEEE International Conference on Automatic Face & Gesture Recognition, 2016.
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@inproceedings{13528693,
title = {FaceNet2ExpNet: Regularizing a Deep Face Recognition Net for Expression Recognition},
author = {{Hui Ding} and {S. Zhou} and {R. Chellappa}},
year = 2016,
month = {9},
booktitle = {IEEE International Conference on Automatic Face & Gesture Recognition},
url = {https://www.semanticscholar.org/paper/1178606d83cc32ca9e99a9ed2aa1b9dd35c11419},
}

Pouya Samangouei and R. Chellappa, “Convolutional neural networks for attribute-based active authentication on mobile devices,” in 2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS), 2016.
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@inproceedings{14465016,
title = {Convolutional neural networks for attribute-based active authentication on mobile devices},
author = {{Pouya Samangouei} and {R. Chellappa}},
year = 2016,
month = {4},
booktitle = {2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS)},
url = {https://www.semanticscholar.org/paper/9b38a536982409358030a97b58be3c9b05922db3},
}

Xingguo Li, Haoming Jiang, Jarvis D. Haupt, R. Arora, Han Liu, Mingyi Hong, and T. Zhao, “On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don’t Worry About its Nonsmooth Loss Function,” in Conference on Uncertainty in Artificial Intelligence, 2016.
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@inproceedings{119301368,
title = {On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don't Worry About its Nonsmooth Loss Function},
author = {{Xingguo Li} and {Haoming Jiang} and {Jarvis D. Haupt} and {R. Arora} and {Han Liu} and {Mingyi Hong} and {T. Zhao}},
year = 2016,
month = {5},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
url = {https://www.semanticscholar.org/paper/8d35a0ba7fae3849f57937fe8efa9e4046ee8ad1},
}

L. F. Yang, R. Arora, V. Braverman, and T. Zhao, “A Brief Review of Popular Optimization Algorithms.” 2016.
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@inproceedings{260498753,
title = {A Brief Review of Popular Optimization Algorithms},
author = {{L. F. Yang} and {R. Arora} and {V. Braverman} and {T. Zhao}},
year = 2016,
booktitle = {},
url = {https://www.semanticscholar.org/paper/639c9de668028da9ce10c013c5fbba6a77f1f33c},
}

Mohammed Senoussaoui, P. Cardinal, N. Dehak, and Alessandro Lameiras Koerich, “Native Language Detection Using the I-Vector Framework,” in Interspeech, 2016.
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@inproceedings{30911736,
title = {Native Language Detection Using the I-Vector Framework},
author = {{Mohammed Senoussaoui} and {P. Cardinal} and {N. Dehak} and {Alessandro Lameiras Koerich}},
year = 2016,
month = {9},
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/8ab395e1889606b76ea7cd2be42cbebb2689076c},
}

Nazre Batool and R. Chellappa, “Modeling of Facial Wrinkles for Applications in Computer Vision.” 2016.
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@inproceedings{148519249,
title = {Modeling of Facial Wrinkles for Applications in Computer Vision},
author = {{Nazre Batool} and {R. Chellappa}},
year = 2016,
booktitle = {},
url = {https://www.semanticscholar.org/paper/d75c22c18a45ab00eefd6b61522715954de3c015},
}

Jingxiao Zheng, Jun-Cheng Chen, Navaneeth Bodla, Vishal M. Patel, and R. Chellappa, “VLAD encoded Deep Convolutional features for unconstrained face verification,” in International Conference on Pattern Recognition, 2016.
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@inproceedings{2998343,
title = {VLAD encoded Deep Convolutional features for unconstrained face verification},
author = {{Jingxiao Zheng} and {Jun-Cheng Chen} and {Navaneeth Bodla} and {Vishal M. Patel} and {R. Chellappa}},
year = 2016,
booktitle = {International Conference on Pattern Recognition},
url = {https://www.semanticscholar.org/paper/a3201e955d6607d383332f3a12a7befa08c5a18c},
}

Z. Tan, N. Dehak, J. Larsen, and Zhanyu Ma, “Proceedings of the First International Workshop on Sensing, Processing and Learning for Intelligent Machines (SPLINE 2016).” 2016.
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@inproceedings{64799953,
title = {Proceedings of the First International Workshop on Sensing, Processing and Learning for Intelligent Machines (SPLINE 2016)},
author = {{Z. Tan} and {N. Dehak} and {J. Larsen} and {Zhanyu Ma}},
year = 2016,
booktitle = {},
url = {https://www.semanticscholar.org/paper/a087c1d1dbedbfb9458e89883fd3059bbf0b1f8f},
}

Christopher Reale, N. Nasrabadi, H. Kwon, and R. Chellappa, “Seeing the Forest from the Trees: A Holistic Approach to Near-Infrared Heterogeneous Face Recognition,” in 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2016.
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@inproceedings{6947249,
title = {Seeing the Forest from the Trees: A Holistic Approach to Near-Infrared Heterogeneous Face Recognition},
author = {{Christopher Reale} and {N. Nasrabadi} and {H. Kwon} and {R. Chellappa}},
year = 2016,
month = {6},
booktitle = {2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
url = {https://www.semanticscholar.org/paper/a8748a79e8d37e395354ba7a8b3038468cb37e1f},
}

Ming-hui Du and R. Chellappa, “Face Association for Videos Using Conditional Random Fields and Max-Margin Markov Networks,” in IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016.
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@inproceedings{17576364,
title = {Face Association for Videos Using Conditional Random Fields and Max-Margin Markov Networks},
author = {{Ming-hui Du} and {R. Chellappa}},
year = 2016,
month = {9},
booktitle = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
url = {https://www.semanticscholar.org/paper/fefaa892f1f3ff78db4da55391f4a76d6536c49a},
}

Patrice Boucher, P. Dufour, P. Plusquellec, N. Dehak, P. Dumouchel, and P. Cardinal, “PHYSIOSTRESS: A multimodal corpus of data on acute stress and physiological activation.” 2016.
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@inproceedings{150655590,
title = {PHYSIOSTRESS: A multimodal corpus of data on acute stress and physiological activation},
author = {{Patrice Boucher} and {P. Dufour} and {P. Plusquellec} and {N. Dehak} and {P. Dumouchel} and {P. Cardinal}},
year = 2016,
booktitle = {},
url = {https://www.semanticscholar.org/paper/c5c225999b6d2ad316fe7693b398e290407a43c3},
}

David A. Broniatowski, Karen Hilyard, and Mark Dredze, “Effective vaccine communication during the disneyland measles outbreak.,” in Vaccine, 2016.
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@inproceedings{12462194,
title = {Effective vaccine communication during the disneyland measles outbreak.},
author = {{David A. Broniatowski} and {Karen Hilyard} and {Mark Dredze}},
year = 2016,
month = {6},
booktitle = {Vaccine},
url = {https://www.semanticscholar.org/paper/a541c0b33ffdbb82f6e536a15e4f9bcb2818e51c},
}

Tomas Figliolia, P. Julián, Gaspar Tognetti, and A. Andreou, “A true Random Number Generator using RTN noise and a sigma delta converter,” in International Symposium on Circuits and Systems, 2016.
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@inproceedings{32252301,
title = {A true Random Number Generator using RTN noise and a sigma delta converter},
author = {{Tomas Figliolia} and {P. Julián} and {Gaspar Tognetti} and {A. Andreou}},
year = 2016,
month = {5},
booktitle = {International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/ca8124f8343a219de726660dc78647bfab84cd47},
}

Xingguo Li, T. Zhao, R. Arora, Han Liu, and Mingyi Hong, “An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization,” in International Conference on Artificial Intelligence and Statistics, 2016.
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title = {An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization},
author = {{Xingguo Li} and {T. Zhao} and {R. Arora} and {Han Liu} and {Mingyi Hong}},
year = 2016,
month = {7},
booktitle = {International Conference on Artificial Intelligence and Statistics},
url = {https://www.semanticscholar.org/paper/5d4b71408a79c6780c5e238c871d431504425195},
}

Jun-Cheng Chen, Jingxiao Zheng, Vishal M. Patel, and R. Chellappa, “Fisher vector encoded deep convolutional features for unconstrained face verification,” in International Conference on Information Photonics, 2016.
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@inproceedings{10653358,
title = {Fisher vector encoded deep convolutional features for unconstrained face verification},
author = {{Jun-Cheng Chen} and {Jingxiao Zheng} and {Vishal M. Patel} and {R. Chellappa}},
year = 2016,
month = {8},
booktitle = {International Conference on Information Photonics},
url = {https://www.semanticscholar.org/paper/ea03a569272d329090fe60d6bff8d119e18057d7},
}

Stephen Shum, David F. Harwath, N. Dehak, and James R. Glass, “On the Use of Acoustic Unit Discovery for Language Recognition,” in IEEE/ACM Transactions on Audio Speech and Language Processing, 2016.
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@inproceedings{15121969,
title = {On the Use of Acoustic Unit Discovery for Language Recognition},
author = {{Stephen Shum} and {David F. Harwath} and {N. Dehak} and {James R. Glass}},
year = 2016,
month = {6},
booktitle = {IEEE/ACM Transactions on Audio Speech and Language Processing},
url = {https://www.semanticscholar.org/paper/0c45609bd0f4216d6a50cc2b191d76be55cafa48},
}

Supreeth Achar, H. Ackermann, Antonio Agudo, N. Ahuja, Zeynep Akata, Alahari Karteek, P. Aljabar, Y. Aloimonos, Jose Alvarez, Alexander Andreopoulos, Bjoern Andres, A. Angelova, Stanislaw Antol, Relja Arandjelović, P. Arbelaez, Devansh Arpit, S. Asif, Freddie Åström, L. Astola, V. Athitsos, Mathieu Aubry, S. Avidan, Arunava Banerjee, J. Barreto, Jorge Batista, Dhruv Batra, Maximilian Baust, Vasileios Belagiannis, Samy Bengio, Fabian Benitez-Quiroz, S. Biasotti, Hakan Bilen, Guillaume-Alexandre Bilodeau, Federica Bogo, Lubomir D. Bourdev, Y-Lan Boureau, Edmond Boyer, Steve Branson, Ernesto Brau, José Henrique Brito, G. Brostow, Michael Brown, Z. Bylinskii, Martin Byröd, Octavia Camps, Liangliang Cao, Guillaume Caron, João Carreira, D. Casas, Luka Cehovin, Hakan Cevikalp, Antonin Chambolle, Jason Chang, G. Charpiat, B. Chaudhuri, R. Chellappa, Jie Chen, A. Cherian, Guilhem Chéron, Cheng-Chieh Chiang, J. Chiverton, Minsu Cho, Wongun Choi, Yejin Choi, Wenchang Chu, Yu Chuang, R. G. Cinbis, T. Cootes, J. Corso, Andrew Cotter, Aaron C. Courville, David J. Crandall, Rozenn Dahyot, Yuchao Dai, Jifeng Dai, and M. Daoudi, “Appreciation to IJCV Reviewers of 2016,” in International Journal of Computer Vision, 2016.
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@inproceedings{52847658,
title = {Appreciation to IJCV Reviewers of 2016},
author = {{Supreeth Achar} and {H. Ackermann} and {Antonio Agudo} and {N. Ahuja} and {Zeynep Akata} and {Alahari Karteek} and {P. Aljabar} and {Y. Aloimonos} and {Jose Alvarez} and {Alexander Andreopoulos} and {Bjoern Andres} and {A. Angelova} and {Stanislaw Antol} and {Relja Arandjelović} and {P. Arbelaez} and {Devansh Arpit} and {S. Asif} and {Freddie Åström} and {L. Astola} and {V. Athitsos} and {Mathieu Aubry} and {S. Avidan} and {Arunava Banerjee} and {J. Barreto} and {Jorge Batista} and {Dhruv Batra} and {Maximilian Baust} and {Vasileios Belagiannis} and {Samy Bengio} and {Fabian Benitez-Quiroz} and {S. Biasotti} and {Hakan Bilen} and {Guillaume-Alexandre Bilodeau} and {Federica Bogo} and {Lubomir D. Bourdev} and {Y-Lan Boureau} and {Edmond Boyer} and {Steve Branson} and {Ernesto Brau} and {José Henrique Brito} and {G. Brostow} and {Michael Brown} and {Z. Bylinskii} and {Martin Byröd} and {Octavia Camps} and {Liangliang Cao} and {Guillaume Caron} and {João Carreira} and {D. Casas} and {Luka Cehovin} and {Hakan Cevikalp} and {Antonin Chambolle} and {Jason Chang} and {G. Charpiat} and {B. Chaudhuri} and {R. Chellappa} and {Jie Chen} and {A. Cherian} and {Guilhem Chéron} and {Cheng-Chieh Chiang} and {J. Chiverton} and {Minsu Cho} and {Wongun Choi} and {Yejin Choi} and {Wenchang Chu} and {Yu Chuang} and {R. G. Cinbis} and {T. Cootes} and {J. Corso} and {Andrew Cotter} and {Aaron C. Courville} and {David J. Crandall} and {Rozenn Dahyot} and {Yuchao Dai} and {Jifeng Dai} and {M. Daoudi}},
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booktitle = {International Journal of Computer Vision},
url = {https://www.semanticscholar.org/paper/6477881b6bae80423b69a8d8a24b7f4b1f1f068a},
}

U. Mahbub, Vishal M. Patel, Deepak Chandra, Brandon Barbello, and R. Chellappa, “Partial face detection for continuous authentication,” in International Conference on Information Photonics, 2016.
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@inproceedings{2614779,
title = {Partial face detection for continuous authentication},
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year = 2016,
month = {3},
booktitle = {International Conference on Information Photonics},
url = {https://www.semanticscholar.org/paper/91d898681bcb1ff3f6b1cfd46a74e841bc619ea5},
}

L. Burget, S. Khudanpur, N. Dehak, J. Trmal, R. Haeb-Umbach, Graham Neubig, Shinji Watanabe, D. Mochihashi, T. Shinozaki, Ming Sun, Chunxi Liu, Matthew Wiesner, R. Pappagari, Lucas Ondel, M. Hannemann, Santosh Kesiraju, Thomas Glarner, Leda Sari, Jinyi Yang, Ondřej Cífka, Yibo Yang, and Alena Rott, “Building Speech Recognition System from Untranscribed Data Report from JHU workshop 2016.” 2016.
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@inproceedings{231778345,
title = {Building Speech Recognition System from Untranscribed Data Report from JHU workshop 2016},
author = {{L. Burget} and {S. Khudanpur} and {N. Dehak} and {J. Trmal} and {R. Haeb-Umbach} and {Graham Neubig} and {Shinji Watanabe} and {D. Mochihashi} and {T. Shinozaki} and {Ming Sun} and {Chunxi Liu} and {Matthew Wiesner} and {R. Pappagari} and {Lucas Ondel} and {M. Hannemann} and {Santosh Kesiraju} and {Thomas Glarner} and {Leda Sari} and {Jinyi Yang} and {Ondřej Cífka} and {Yibo Yang} and {Alena Rott}},
year = 2016,
booktitle = {},
url = {https://www.semanticscholar.org/paper/2a0cb1a1e78b77fe9981e4935410cf3ea900e370},
}

A. Andreou, Andrew A. Dykman, Kate D. Fischl, Guillaume Garreau, Daniel R. Mendat, G. Orchard, A. Cassidy, P. Merolla, J. Arthur, Rodrigo Alvarez-Icaza, Bryan L. Jackson, and D. Modha, “Real-time sensory information processing using the TrueNorth Neurosynaptic System,” in International Symposium on Circuits and Systems, 2016.
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@inproceedings{29335047,
title = {Real-time sensory information processing using the TrueNorth Neurosynaptic System},
author = {{A. Andreou} and {Andrew A. Dykman} and {Kate D. Fischl} and {Guillaume Garreau} and {Daniel R. Mendat} and {G. Orchard} and {A. Cassidy} and {P. Merolla} and {J. Arthur} and {Rodrigo Alvarez-Icaza} and {Bryan L. Jackson} and {D. Modha}},
year = 2016,
month = {5},
booktitle = {International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/d14c058fd745865522433d79e2320e4945cd005b},
}

Raviteja Vemulapalli, Oncel Tuzel, Ming-Yu Liu, and R. Chellappa, “Gaussian Conditional Random Field Network for Semantic Segmentation,” in Computer Vision and Pattern Recognition, 2016.
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@inproceedings{5806785,
title = {Gaussian Conditional Random Field Network for Semantic Segmentation},
author = {{Raviteja Vemulapalli} and {Oncel Tuzel} and {Ming-Yu Liu} and {R. Chellappa}},
year = 2016,
month = {6},
booktitle = {Computer Vision and Pattern Recognition},
url = {https://www.semanticscholar.org/paper/e48cd65147c25f45f9270cad76e2983a2a510b25},
}

Mark Dredze, M. García-Herranz, A. Rutherford, and Gideon Mann, “Twitter as a Source of Global Mobility Patterns for Social Good,” in arXiv.org, 2016.
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@inproceedings{14589094,
title = {Twitter as a Source of Global Mobility Patterns for Social Good},
author = {{Mark Dredze} and {M. García-Herranz} and {A. Rutherford} and {Gideon Mann}},
year = 2016,
month = {6},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/aec47e63de4dbfeda50b03360c178ab49ff73c8e},
}

Keisuke Sakaguchi, Kevin Duh, Matt Post, and Benjamin Van Durme, “Robsut Wrod Reocginiton via Semi-Character Recurrent Neural Network,” in AAAI Conference on Artificial Intelligence, 2016.
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@inproceedings{11217839,
title = {Robsut Wrod Reocginiton via Semi-Character Recurrent Neural Network},
author = {{Keisuke Sakaguchi} and {Kevin Duh} and {Matt Post} and {Benjamin Van Durme}},
year = 2016,
month = {8},
booktitle = {AAAI Conference on Artificial Intelligence},
url = {https://www.semanticscholar.org/paper/711e6e9e2fb1f4ab7238cdd556002ae36deeece7},
}

Nanyun Peng and Mark Dredze, “Multi-task Multi-domain Representation Learning for Sequence Tagging,” in arXiv.org, 2016.
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@inproceedings{487450,
title = {Multi-task Multi-domain Representation Learning for Sequence Tagging},
author = {{Nanyun Peng} and {Mark Dredze}},
year = 2016,
month = {8},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/58a644686a9c44708aff98f019602fa9553e88ff},
}

S. Sankaranarayanan, A. Alavi, C. Castillo, and R. Chellappa, “Triplet probabilistic embedding for face verification and clustering,” in 2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS), 2016.
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@inproceedings{15620656,
title = {Triplet probabilistic embedding for face verification and clustering},
author = {{S. Sankaranarayanan} and {A. Alavi} and {C. Castillo} and {R. Chellappa}},
year = 2016,
month = {4},
booktitle = {2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS)},
url = {https://www.semanticscholar.org/paper/44078d0daed8b13114cffb15b368acc467f96351},
}

R. Arora, Poorya Mianjy, and T. V. Marinov, “Stochastic Optimization for Multiview Representation Learning using Partial Least Squares,” in International Conference on Machine Learning, 2016.
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@inproceedings{11416787,
title = {Stochastic Optimization for Multiview Representation Learning using Partial Least Squares},
author = {{R. Arora} and {Poorya Mianjy} and {T. V. Marinov}},
year = 2016,
month = {6},
booktitle = {International Conference on Machine Learning},
url = {https://www.semanticscholar.org/paper/50b19700129ba7806f1a3a0ae4015d35fcb42eca},
}

J. Ayers, B. Althouse, Mark Dredze, E. Leas, and S. Noar, “News and Internet Searches About Human Immunodeficiency Virus After Charlie Sheen’s Disclosure.,” in JAMA Internal Medicine, 2016.
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@inproceedings{40408108,
title = {News and Internet Searches About Human Immunodeficiency Virus After Charlie Sheen's Disclosure.},
author = {{J. Ayers} and {B. Althouse} and {Mark Dredze} and {E. Leas} and {S. Noar}},
year = 2016,
month = {4},
booktitle = {JAMA Internal Medicine},
url = {https://www.semanticscholar.org/paper/cfb27c8b4a5856ad2150076afca7ea16671b16e3},
}

R. Chellappa, A. Heyden, D. Laurendeau, M. Felsberg, and M. Borga, “Special issue on ICPR 2014 awarded papers,” in Pattern Recognition Letters, 2016.
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@inproceedings{207329778,
title = {Special issue on ICPR 2014 awarded papers},
author = {{R. Chellappa} and {A. Heyden} and {D. Laurendeau} and {M. Felsberg} and {M. Borga}},
year = 2016,
month = {3},
booktitle = {Pattern Recognition Letters},
url = {https://www.semanticscholar.org/paper/3260a88943ef95658482dd938a068cf2b2f75187},
}

Xingguo Li, Jarvis D. Haupt, R. Arora, Han Liu, Mingyi Hong, and T. Zhao, “A First Order Free Lunch for SQRT-Lasso,” in arXiv.org, 2016.
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@inproceedings{12469554,
title = {A First Order Free Lunch for SQRT-Lasso},
author = {{Xingguo Li} and {Jarvis D. Haupt} and {R. Arora} and {Han Liu} and {Mingyi Hong} and {T. Zhao}},
year = 2016,
month = {5},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/c66d62b3345c67c36e209a55670eaea09413d68c},
}

N. Dehak, “I-Vector Representation Based on GMM and DNN for Audio Classification,” in The Speaker and Language Recognition Workshop, 2016.
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@inproceedings{51872123,
title = {I-Vector Representation Based on GMM and DNN for Audio Classification},
author = {{N. Dehak}},
year = 2016,
booktitle = {The Speaker and Language Recognition Workshop},
url = {https://www.semanticscholar.org/paper/5fa0fad2020bbffb70d33152fe80085c213f75fa},
}

C. Morimoto and R. Chellappa, “Fast Image Stabilization and Mosaicking.” 2016.
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@inproceedings{180260851,
title = {Fast Image Stabilization and Mosaicking},
author = {{C. Morimoto} and {R. Chellappa}},
year = 2016,
booktitle = {},
url = {https://www.semanticscholar.org/paper/68c287c03623610469673d2b3b27b2ff6468001e},
}

Alarcão, Anna Aljanaki, J. Allbeck, Miguel A. Alonso-Arévalo, M. Amer, R. Amini, M. Ammi, E. André, Oya Aran, Ognjen Arandjelovíc, B. Arnrich, J. Aronoff, T. Artières, Sadjad Asghari Esfeden, S. Asteriadis, Yadid Ayzenberg, Kévin Bailly, G. Bailly, A. Balahur, Tadas Baltru, X. Burgos-Artizzu, Mihai Burzo, C. Busso, Iván Cantador, A. Cardoso, G. Caridakis, Elín Carstensdóttir, O. Çeliktutan, G. Chanel, R. Chellali, R. Chellappa, J. Chen, Min Chen, Yixin Chen, M. Chetouani, W. Chu, P. Cipresso, Luísa Coheur, J. Cohn, David Cooper, D. Cosker, M. Courgeon, E. Coutinho, David Coyle, M. Cristani, D. Croce, J. Crowe, A. Cullen, N. Cummins, N. Dael, I. Daly, Shyamali Mandal, M. Dcosta, C. Melo, R. Delgado, E. Dellandréa, Jun Deng, Abhinav Dhall, H. Dibeklioğlu, Karthik Dinakar, Sidney K. D’Mello, Chelsea Dobbins, Qunxi Dong, K. Drossos, Shichuan Du, Damien Dupré, S. Ehrlich, Carsten Eickhoff, Birgit Lugrin, J. Epps, Marchi Erik, A. Esposito, Andrea Esuli, F. Eyben, A. Fagg, and H. Fang, “2015 reviewers list,” in TCBB, 2016.
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@inproceedings{46315564,
title = {2015 reviewers list},
author = {{Alarcão} and {Anna Aljanaki} and {J. Allbeck} and {Miguel A. Alonso-Arévalo} and {M. Amer} and {R. Amini} and {M. Ammi} and {E. André} and {Oya Aran} and {Ognjen Arandjelovíc} and {B. Arnrich} and {J. Aronoff} and {T. Artières} and {Sadjad Asghari Esfeden} and {S. Asteriadis} and {Yadid Ayzenberg} and {Kévin Bailly} and {G. Bailly} and {A. Balahur} and {Tadas Baltru} and {X. Burgos-Artizzu} and {Mihai Burzo} and {C. Busso} and {Iván Cantador} and {A. Cardoso} and {G. Caridakis} and {Elín Carstensdóttir} and {O. Çeliktutan} and {G. Chanel} and {R. Chellali} and {R. Chellappa} and {J. Chen} and {Min Chen} and {Yixin Chen} and {M. Chetouani} and {W. Chu} and {P. Cipresso} and {Luísa Coheur} and {J. Cohn} and {David Cooper} and {D. Cosker} and {M. Courgeon} and {E. Coutinho} and {David Coyle} and {M. Cristani} and {D. Croce} and {J. Crowe} and {A. Cullen} and {N. Cummins} and {N. Dael} and {I. Daly} and {Shyamali Mandal} and {M. Dcosta} and {C. Melo} and {R. Delgado} and {E. Dellandréa} and {Jun Deng} and {Abhinav Dhall} and {H. Dibeklioğlu} and {Karthik Dinakar} and {Sidney K. D’Mello} and {Chelsea Dobbins} and {Qunxi Dong} and {K. Drossos} and {Shichuan Du} and {Damien Dupré} and {S. Ehrlich} and {Carsten Eickhoff} and {Birgit Lugrin} and {J. Epps} and {Marchi Erik} and {A. Esposito} and {Andrea Esuli} and {F. Eyben} and {A. Fagg} and {H. Fang}},
year = 2016,
booktitle = {TCBB},
url = {https://www.semanticscholar.org/paper/044c4b800741bbd34e23274b84411709c974ca68},
}

Peter F. Schulam and R. Arora, “Disease Trajectory Maps,” in Neural Information Processing Systems, 2016.
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@inproceedings{477065,
title = {Disease Trajectory Maps},
author = {{Peter F. Schulam} and {R. Arora}},
year = 2016,
month = {6},
booktitle = {Neural Information Processing Systems},
url = {https://www.semanticscholar.org/paper/930e358f69183e86a3fe10a54dbac7d9c0ef6276},
}

Adrian Benton, Michael J. Paul, Braden Hancock, and Mark Dredze, “Collective Supervision of Topic Models for Predicting Surveys with Social Media,” in AAAI Conference on Artificial Intelligence, 2016.
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@inproceedings{17781514,
title = {Collective Supervision of Topic Models for Predicting Surveys with Social Media},
author = {{Adrian Benton} and {Michael J. Paul} and {Braden Hancock} and {Mark Dredze}},
year = 2016,
month = {2},
booktitle = {AAAI Conference on Artificial Intelligence},
url = {https://www.semanticscholar.org/paper/1818bdee5bb946207b51a434e734fe60eacb9688},
}

Nanyun Peng and Mark Dredze, “Improving Named Entity Recognition for Chinese Social Media with Word Segmentation Representation Learning.” 2016.
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@inproceedings{204940654,
title = {Improving Named Entity Recognition for Chinese Social Media with Word Segmentation Representation Learning},
author = {{Nanyun Peng} and {Mark Dredze}},
year = 2016,
month = {3},
booktitle = {},
url = {https://www.semanticscholar.org/paper/4ba70b8738aa528ecaf51e51bef0511fd1a36936},
}

Soumyadip Sengupta, Jun-Cheng Chen, C. Castillo, Vishal M. Patel, R. Chellappa, and D. Jacobs, “Frontal to profile face verification in the wild,” in IEEE Workshop/Winter Conference on Applications of Computer Vision, 2016.
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@inproceedings{6544744,
title = {Frontal to profile face verification in the wild},
author = {{Soumyadip Sengupta} and {Jun-Cheng Chen} and {C. Castillo} and {Vishal M. Patel} and {R. Chellappa} and {D. Jacobs}},
year = 2016,
month = {3},
booktitle = {IEEE Workshop/Winter Conference on Applications of Computer Vision},
url = {https://www.semanticscholar.org/paper/100105d6c97b23059f7aa70589ead2f61969fbc3},
}

Takafumi Moriya, Tomohiro Tanaka, T. Shinozaki, Shinji Watanabe, and Kevin Duh, “Automation of system building for state-of-the-art large vocabulary speech recognition using evolution strategy,” in Automatic Speech Recognition & Understanding, 2015.
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@inproceedings{764181,
title = {Automation of system building for state-of-the-art large vocabulary speech recognition using evolution strategy},
author = {{Takafumi Moriya} and {Tomohiro Tanaka} and {T. Shinozaki} and {Shinji Watanabe} and {Kevin Duh}},
year = 2015,
month = {12},
booktitle = {Automatic Speech Recognition & Understanding},
url = {https://www.semanticscholar.org/paper/9976ed0d88a4156ecdd3ebe39714c5fb4a5a0246},
}

Xiaoyi Wu, Yuji Matsumoto, Kevin Duh, and Hiroyuki Shindo, “An Improved Hierarchical Word Sequence Language Model Using Word Association,” in International Conference on Statistical Language and Speech Processing, 2015.
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@inproceedings{31406442,
title = {An Improved Hierarchical Word Sequence Language Model Using Word Association},
author = {{Xiaoyi Wu} and {Yuji Matsumoto} and {Kevin Duh} and {Hiroyuki Shindo}},
year = 2015,
month = {11},
booktitle = {International Conference on Statistical Language and Speech Processing},
url = {https://www.semanticscholar.org/paper/6cf61b5bb1c54113ae049d8fdd2413ec20c69bc6},
}

Hani Bakhshaee, J. Seo, Chi Zhu, Nathaniel Welsh, Guillaume Garreau, Gaspar Tognetti, A. Andreou, and R. Mittal, “Fluid Dynamics of the Generation and Transmission of Heart Sounds: (1) A Cardiothoracic Phantom Based Study of Aortic Stenosis Murmurs,” in Bulletin of the American Physical Society, 2015.
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@inproceedings{125456831,
title = {Fluid Dynamics of the Generation and Transmission of Heart Sounds: (1) A Cardiothoracic Phantom Based Study of Aortic Stenosis Murmurs},
author = {{Hani Bakhshaee} and {J. Seo} and {Chi Zhu} and {Nathaniel Welsh} and {Guillaume Garreau} and {Gaspar Tognetti} and {A. Andreou} and {R. Mittal}},
year = 2015,
month = {11},
booktitle = {Bulletin of the American Physical Society},
url = {https://www.semanticscholar.org/paper/2a4c65f1195c40b25531401755c7766fa1faca46},
}

Xiaodong Liu, Fei Cheng, Kevin Duh, and Yuji Matsumoto, “A Hybrid Ranking Approach to Chinese Spelling Check,” in ACM Trans. Asian Low Resour. Lang. Inf. Process., 2015.
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@inproceedings{15663836,
title = {A Hybrid Ranking Approach to Chinese Spelling Check},
author = {{Xiaodong Liu} and {Fei Cheng} and {Kevin Duh} and {Yuji Matsumoto}},
year = 2015,
month = {11},
booktitle = {ACM Trans. Asian Low Resour. Lang. Inf. Process.},
url = {https://www.semanticscholar.org/paper/122ab5855c3ed0e0f6edd0c587ace31633de0ef8},
}

F. Yung, K. Duh, and Y. Matsumoto, “Crosslingual Annotation and Analysis of Implicit Discourse Connectives for Machine Translation,” in Proceedings of the Second Workshop on Discourse in Machine Translation, Lisbon, Portugal, 2015, p. 142–152. doi:10.18653/v1/W15-2519
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@inproceedings{yung-etal-2015-crosslingual,
title = "Crosslingual Annotation and Analysis of Implicit Discourse Connectives for Machine Translation",
author = "Yung, Frances and
Duh, Kevin and
Matsumoto, Yuji",
editor = "Webber, Bonnie and
Carpuat, Marine and
Popescu-Belis, Andrei and
Hardmeier, Christian",
booktitle = "Proceedings of the Second Workshop on Discourse in Machine Translation",
month = sep,
year = "2015",
address = "Lisbon, Portugal",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W15-2519",
doi = "10.18653/v1/W15-2519",
pages = "142--152",
}

M. R. Gormley, M. Yu, and M. Dredze, “Improved Relation Extraction with Feature-Rich Compositional Embedding Models,” in Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, Lisbon, Portugal, 2015, p. 1774–1784. doi:10.18653/v1/D15-1205
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@inproceedings{gormley-etal-2015-improved,
title = "Improved Relation Extraction with Feature-Rich Compositional Embedding Models",
author = "Gormley, Matthew R. and
Yu, Mo and
Dredze, Mark",
editor = "M{\`a}rquez, Llu{\'\i}s and
Callison-Burch, Chris and
Su, Jian",
booktitle = "Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing",
month = sep,
year = "2015",
address = "Lisbon, Portugal",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D15-1205",
doi = "10.18653/v1/D15-1205",
pages = "1774--1784",
}

N. Peng and M. Dredze, “Named Entity Recognition for Chinese Social Media with Jointly Trained Embeddings,” in Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, Lisbon, Portugal, 2015, p. 548–554. doi:10.18653/v1/D15-1064
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@inproceedings{peng-dredze-2015-named,
title = "Named Entity Recognition for {C}hinese Social Media with Jointly Trained Embeddings",
author = "Peng, Nanyun and
Dredze, Mark",
editor = "M{\`a}rquez, Llu{\'\i}s and
Callison-Burch, Chris and
Su, Jian",
booktitle = "Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing",
month = sep,
year = "2015",
address = "Lisbon, Portugal",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D15-1064",
doi = "10.18653/v1/D15-1064",
pages = "548--554",
}

N. Peng, R. Cotterell, and J. Eisner, “Dual Decomposition Inference for Graphical Models over Strings,” in Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Lisbon, 2015, p. 917–927. doi:10.18653/v1/D15-1108
[BibTeX] [Link]

@InProceedings{peng-cotterell-eisner-2015,
aclid = "D15-1108",
doi = "10.18653/v1/D15-1108",
author = "Nanyun Peng and Ryan Cotterell and Jason Eisner",
title = "Dual Decomposition Inference for Graphical Models over
Strings",
booktitle = "Proceedings of the Conference on Empirical Methods in
Natural Language Processing (EMNLP)",
pages = "917--927",
year = "2015",
month = sep,
address = "Lisbon",
URL = "http://cs.jhu.edu/~jason/papers/#peng-cotterell-eisner-2015",
}

F. Cheng, K. Duh, and Y. Matsumoto, “Synthetic Word Parsing Improves Chinese Word Segmentation,” in Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers), Beijing, China, 2015, p. 262–267. doi:10.3115/v1/P15-2043
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@inproceedings{cheng-etal-2015-synthetic,
title = "Synthetic Word Parsing Improves {C}hinese Word Segmentation",
author = "Cheng, Fei and
Duh, Kevin and
Matsumoto, Yuji",
editor = "Zong, Chengqing and
Strube, Michael",
booktitle = "Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)",
month = jul,
year = "2015",
address = "Beijing, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P15-2043",
doi = "10.3115/v1/P15-2043",
pages = "262--267",
}

H. Ouchi, H. Shindo, K. Duh, and Y. Matsumoto, “Joint Case Argument Identification for Japanese Predicate Argument Structure Analysis,” in Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), Beijing, China, 2015, p. 961–970. doi:10.3115/v1/P15-1093
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@inproceedings{ouchi-etal-2015-joint,
title = "Joint Case Argument Identification for {J}apanese Predicate Argument Structure Analysis",
author = "Ouchi, Hiroki and
Shindo, Hiroyuki and
Duh, Kevin and
Matsumoto, Yuji",
editor = "Zong, Chengqing and
Strube, Michael",
booktitle = "Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)",
month = jul,
year = "2015",
address = "Beijing, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P15-1093",
doi = "10.3115/v1/P15-1093",
pages = "961--970",
}

N. Peng, M. Yu, and M. Dredze, “An Empirical Study of Chinese Name Matching and Applications,” in Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers), Beijing, China, 2015, p. 377–383. doi:10.3115/v1/P15-2062
[BibTeX] [Link]

@inproceedings{peng-etal-2015-empirical,
title = "An Empirical Study of {C}hinese Name Matching and Applications",
author = "Peng, Nanyun and
Yu, Mo and
Dredze, Mark",
editor = "Zong, Chengqing and
Strube, Michael",
booktitle = "Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)",
month = jul,
year = "2015",
address = "Beijing, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P15-2062",
doi = "10.3115/v1/P15-2062",
pages = "377--383",
}

E. Pavlick, T. Wolfe, P. Rastogi, C. Callison-Burch, M. Dredze, and B. Van Durme, “FrameNet+: Fast Paraphrastic Tripling of FrameNet,” in Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers), Beijing, China, 2015, p. 408–413. doi:10.3115/v1/P15-2067
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@inproceedings{pavlick-etal-2015-framenet,
title = "{F}rame{N}et+: Fast Paraphrastic Tripling of {F}rame{N}et",
author = "Pavlick, Ellie and
Wolfe, Travis and
Rastogi, Pushpendre and
Callison-Burch, Chris and
Dredze, Mark and
Van Durme, Benjamin",
editor = "Zong, Chengqing and
Strube, Michael",
booktitle = "Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)",
month = jul,
year = "2015",
address = "Beijing, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P15-2067",
doi = "10.3115/v1/P15-2067",
pages = "408--413",
}

F. Yung, K. Duh, and Y. Matsumoto, “Sequential Annotation and Chunking of Chinese Discourse Structure,” in Proceedings of the Eighth SIGHAN Workshop on Chinese Language Processing, Beijing, China, 2015, p. 1–6. doi:10.18653/v1/W15-3101
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@inproceedings{yung-etal-2015-sequential,
title = "Sequential Annotation and Chunking of {C}hinese Discourse Structure",
author = "Yung, Frances and
Duh, Kevin and
Matsumoto, Yuji",
editor = "Yu, Liang-Chih and
Sui, Zhifang and
Zhang, Yue and
Ng, Vincent",
booktitle = "Proceedings of the Eighth {SIGHAN} Workshop on {C}hinese Language Processing",
month = jul,
year = "2015",
address = "Beijing, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W15-3101",
doi = "10.18653/v1/W15-3101",
pages = "1--6",
}

N. Peng, F. Ferraro, M. Yu, N. Andrews, J. DeYoung, M. Thomas, M. R. Gormley, T. Wolfe, C. Harman, B. Van Durme, and M. Dredze, “A Concrete Chinese NLP Pipeline,” in Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations, Denver, Colorado, 2015, p. 86–90. doi:10.3115/v1/N15-3018
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@inproceedings{peng-etal-2015-concrete,
title = "A Concrete {C}hinese {NLP} Pipeline",
author = "Peng, Nanyun and
Ferraro, Francis and
Yu, Mo and
Andrews, Nicholas and
DeYoung, Jay and
Thomas, Max and
Gormley, Matthew R. and
Wolfe, Travis and
Harman, Craig and
Van Durme, Benjamin and
Dredze, Mark",
editor = "Gerber, Matt and
Havasi, Catherine and
Lacatusu, Finley",
booktitle = "Proceedings of the 2015 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Demonstrations",
month = jun,
year = "2015",
address = "Denver, Colorado",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N15-3018",
doi = "10.3115/v1/N15-3018",
pages = "86--90",
}

R. Cotterell and J. Eisner, “Penalized Expectation Propagation for Graphical Models Over Strings,” in Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT), Denver, 2015, p. 932–942. doi:10.3115/v1/N15-1094
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@InProceedings{cotterell-eisner-2015,
aclid = "N15-1094",
doi = "10.3115/v1/N15-1094",
author = "Ryan Cotterell and Jason Eisner",
title = "Penalized Expectation Propagation for Graphical Models
Over Strings",
booktitle = "Proceedings of the 2015 Conference of the North
American Chapter of the Association for Computational
Linguistics: Human Language Technologies (NAACL-HLT)",
pages = "932--942",
note = "Supplementary material (11 pages) also available",
year = "2015",
month = jun,
address = "Denver",
URL = "http://cs.jhu.edu/~jason/papers/#cotterell-eisner-2015",
}

David A. Broniatowski, Michael J. Paul, and Mark Dredze, “Machine learning:Trends, perspectives, and prospects.” 2015.
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@inproceedings{63987411,
title = {Machine learning:Trends, perspectives, and prospects},
author = {{David A. Broniatowski} and {Michael J. Paul} and {Mark Dredze}},
year = 2015,
booktitle = {},
url = {https://www.semanticscholar.org/paper/a89762ae8574f4b55a1814e72750bfc3be57a70d},
}

M. Villemur, M. D. Federico, P. Julián, A. Andreou, F. Masson, and E. Nebot, “Design of a vanishing point algorithm for custom ASIC,” in Annual Conference on Information Sciences and Systems, 2015.
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@inproceedings{11812867,
title = {Design of a vanishing point algorithm for custom ASIC},
author = {{M. Villemur} and {M. D. Federico} and {P. Julián} and {A. Andreou} and {F. Masson} and {E. Nebot}},
year = 2015,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/8defdb81dbd9974a83c40ba16729c1fed79817e0},
}

A. Andreou, T. Abraham, W. R. Thompson, J. Seo, and R. Mittal, “Mapping the cardiac acousteome: An overview of technologies, tools and methods,” in Annual Conference on Information Sciences and Systems, 2015.
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@inproceedings{7252198,
title = {Mapping the cardiac acousteome: An overview of technologies, tools and methods},
author = {{A. Andreou} and {T. Abraham} and {W. R. Thompson} and {J. Seo} and {R. Mittal}},
year = 2015,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/cd4f57bde7af3a2c33f3f676ae607ee82d61651b},
}

J. Molin, Tomas Figliolia, Kayode A. Sanni, I. Doxas, A. Andreou, and R. Etienne-Cummings, “FPGA emulation of a spike-based, stochastic system for real-time image dewarping,” in Midwest Symposium on Circuits and Systems, 2015.
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@inproceedings{36076568,
title = {FPGA emulation of a spike-based, stochastic system for real-time image dewarping},
author = {{J. Molin} and {Tomas Figliolia} and {Kayode A. Sanni} and {I. Doxas} and {A. Andreou} and {R. Etienne-Cummings}},
year = 2015,
month = {8},
booktitle = {Midwest Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/b8cf4bc69d6801dab3e3467c815cbc48b40598e0},
}

G. Coppersmith, M. Dredze, C. Harman, and K. Hollingshead, “From ADHD to SAD: Analyzing the Language of Mental Health on Twitter through Self-Reported Diagnoses,” in Proceedings of the 2nd Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality, Denver, Colorado, 2015, p. 1–10. doi:10.3115/v1/W15-1201
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@inproceedings{coppersmith-etal-2015-adhd,
title = "From {ADHD} to {SAD}: Analyzing the Language of Mental Health on {T}witter through Self-Reported Diagnoses",
author = "Coppersmith, Glen and
Dredze, Mark and
Harman, Craig and
Hollingshead, Kristy",
booktitle = "Proceedings of the 2nd Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality",
month = jun # " 5",
year = "2015",
address = "Denver, Colorado",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W15-1201",
doi = "10.3115/v1/W15-1201",
pages = "1--10",
}

Travis Wolfe, Mark Dredze, J. Mayfield, Paul McNamee, Craig Harman, Timothy W. Finin, and Benjamin Van Durme, “Interactive Knowledge Base Population,” in arXiv.org, 2015.
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@inproceedings{6681632,
title = {Interactive Knowledge Base Population},
author = {{Travis Wolfe} and {Mark Dredze} and {J. Mayfield} and {Paul McNamee} and {Craig Harman} and {Timothy W. Finin} and {Benjamin Van Durme}},
year = 2015,
month = {5},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/b9d1d9d618c504b669e1d78e9fc6f5efa51e8ca5},
}

K. Yao, Trevor Cohn, Katerina Vylomova, Kevin Duh, and Chris Dyer, “Depth-Gated Recurrent Neural Networks.” 2015.
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@inproceedings{15641534,
title = {Depth-Gated Recurrent Neural Networks},
author = {{K. Yao} and {Trevor Cohn} and {Katerina Vylomova} and {Kevin Duh} and {Chris Dyer}},
year = 2015,
month = {8},
booktitle = {},
url = {https://www.semanticscholar.org/paper/b777a55505ee2ffb4f8f9ada916e4e4a5f13a4ed},
}

Daniel R. Mendat, S. Chin, S. Furber, and A. Andreou, “Markov Chain Monte Carlo inference on graphical models using event-based processing on the SpiNNaker neuromorphic architecture,” in Annual Conference on Information Sciences and Systems, 2015.
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@inproceedings{3660684,
title = {Markov Chain Monte Carlo inference on graphical models using event-based processing on the SpiNNaker neuromorphic architecture},
author = {{Daniel R. Mendat} and {S. Chin} and {S. Furber} and {A. Andreou}},
year = 2015,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/c60e3e0ea9c2ea5db70c96a7fda9966ff415181e},
}

NeuroData, Gray William, Martin Jg, Coppersmith Gc, Mark Dredze, J. Bogovic, Jerry L Prince, S. Resnick, C. Priebe, and R. J. Vogelstein, “Connectome Classification using statistical graph theory and machine learning.” 2015.
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@inproceedings{62478138,
title = {Connectome Classification using statistical graph theory and machine learning},
author = {{NeuroData} and {Gray William} and {Martin Jg} and {Coppersmith Gc} and {Mark Dredze} and {J. Bogovic} and {Jerry L Prince} and {S. Resnick} and {C. Priebe} and {R. J. Vogelstein}},
year = 2015,
month = {1},
booktitle = {},
url = {https://www.semanticscholar.org/paper/b8be7a8679577a758da6571e39b5df5abeb460c8},
}

G. Neubig, P. Arthur, and K. Duh, “Multi-Target Machine Translation with Multi-Synchronous Context-free Grammars,” in Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Denver, Colorado, 2015, p. 293–302. doi:10.3115/v1/N15-1033
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@inproceedings{neubig-etal-2015-multi,
title = "Multi-Target Machine Translation with Multi-Synchronous Context-free Grammars",
author = "Neubig, Graham and
Arthur, Philip and
Duh, Kevin",
editor = "Mihalcea, Rada and
Chai, Joyce and
Sarkar, Anoop",
booktitle = "Proceedings of the 2015 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies",
month = may # "{--}" # jun,
year = "2015",
address = "Denver, Colorado",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N15-1033",
doi = "10.3115/v1/N15-1033",
pages = "293--302",
}

X. Liu, J. Gao, X. He, L. Deng, K. Duh, and Y. Wang, “Representation Learning Using Multi-Task Deep Neural Networks for Semantic Classification and Information Retrieval,” in Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Denver, Colorado, 2015, p. 912–921. doi:10.3115/v1/N15-1092
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@inproceedings{liu-etal-2015-representation,
title = "Representation Learning Using Multi-Task Deep Neural Networks for Semantic Classification and Information Retrieval",
author = "Liu, Xiaodong and
Gao, Jianfeng and
He, Xiaodong and
Deng, Li and
Duh, Kevin and
Wang, Ye-yi",
editor = "Mihalcea, Rada and
Chai, Joyce and
Sarkar, Anoop",
booktitle = "Proceedings of the 2015 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies",
month = may # "{--}" # jun,
year = "2015",
address = "Denver, Colorado",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N15-1092",
doi = "10.3115/v1/N15-1092",
pages = "912--921",
}

G. Coppersmith, M. Dredze, C. Harman, K. Hollingshead, and M. Mitchell, “CLPsych 2015 Shared Task: Depression and PTSD on Twitter,” in Proceedings of the 2nd Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality, Denver, Colorado, 2015, p. 31–39. doi:10.3115/v1/W15-1204
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@inproceedings{coppersmith-etal-2015-clpsych,
title = "{CLP}sych 2015 Shared Task: Depression and {PTSD} on {T}witter",
author = "Coppersmith, Glen and
Dredze, Mark and
Harman, Craig and
Hollingshead, Kristy and
Mitchell, Margaret",
booktitle = "Proceedings of the 2nd Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality",
month = jun # " 5",
year = "2015",
address = "Denver, Colorado",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W15-1204",
doi = "10.3115/v1/W15-1204",
pages = "31--39",
}

Hani Bakhshaee, Guillaume Garreau, Gaspar Tognetti, K. Shoele, R. Carrero, T. Kilmar, Chiang-Jiang Zhu, W. R. Thompson, J. Seo, R. Mittal, and A. Andreou, “Mechanical design, instrumentation and measurements from a hemoacoustic cardiac phantom,” in Annual Conference on Information Sciences and Systems, 2015.
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@inproceedings{16886349,
title = {Mechanical design, instrumentation and measurements from a hemoacoustic cardiac phantom},
author = {{Hani Bakhshaee} and {Guillaume Garreau} and {Gaspar Tognetti} and {K. Shoele} and {R. Carrero} and {T. Kilmar} and {Chiang-Jiang Zhu} and {W. R. Thompson} and {J. Seo} and {R. Mittal} and {A. Andreou}},
year = 2015,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/b8f18feef8ea2225063ec977b1271dcb2736122d},
}

Kayode A. Sanni, Guillaume Garreau, J. Molin, and A. Andreou, “Architecture for Character Recognition Using Stochastic Computation.” 2015.
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@inproceedings{62093662,
title = {Architecture for Character Recognition Using Stochastic Computation},
author = {{Kayode A. Sanni} and {Guillaume Garreau} and {J. Molin} and {A. Andreou}},
year = 2015,
booktitle = {},
url = {https://www.semanticscholar.org/paper/f56408962023a53064376969612a2d8c78f2c11a},
}

Mrinal Kumar, Mark Dredze, Glen A. Coppersmith, and M. Choudhury, “Detecting Changes in Suicide Content Manifested in Social Media Following Celebrity Suicides,” in ACM Conference on Hypertext & Social Media, 2015.
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@inproceedings{9752942,
title = {Detecting Changes in Suicide Content Manifested in Social Media Following Celebrity Suicides},
author = {{Mrinal Kumar} and {Mark Dredze} and {Glen A. Coppersmith} and {M. Choudhury}},
year = 2015,
month = {8},
booktitle = {ACM Conference on Hypertext & Social Media},
url = {https://www.semanticscholar.org/paper/2a0b2f1dc84a35a2d186edaf24fae92d8f1883e9},
}

Kayode A. Sanni, Guillaume Garreau, J. Molin, and A. Andreou, “FPGA implementation of a Deep Belief Network architecture for character recognition using stochastic computation,” in Annual Conference on Information Sciences and Systems, 2015.
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@inproceedings{12843544,
title = {FPGA implementation of a Deep Belief Network architecture for character recognition using stochastic computation},
author = {{Kayode A. Sanni} and {Guillaume Garreau} and {J. Molin} and {A. Andreou}},
year = 2015,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/0b963df7a367edb59b83cdc60a02d18252fa9179},
}

Haoyu Wang, E. Hovy, and Mark Dredze, “The Hurricane Sandy Twitter Corpus,” in AAAI Workshop: WWW and Public Health Intelligence, 2015.
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@inproceedings{20529470,
title = {The Hurricane Sandy Twitter Corpus},
author = {{Haoyu Wang} and {E. Hovy} and {Mark Dredze}},
year = 2015,
booktitle = {AAAI Workshop: WWW and Public Health Intelligence},
url = {https://www.semanticscholar.org/paper/bf7f220a2908268a7a1c432a2c2efd81afed6808},
}

Thomas S. Murray, Daniel R. Mendat, P. Pouliquen, and A. Andreou, “The Johns Hopkins University multimodal dataset for human action recognition,” in Defense + Security Symposium, 2015.
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@inproceedings{118259583,
title = {The Johns Hopkins University multimodal dataset for human action recognition},
author = {{Thomas S. Murray} and {Daniel R. Mendat} and {P. Pouliquen} and {A. Andreou}},
year = 2015,
month = {5},
booktitle = {Defense + Security Symposium},
url = {https://www.semanticscholar.org/paper/fa944a7ffa9e081e7cbd2ccfeea5421adcb6fbe2},
}

K. Yao, Trevor Cohn, Ekaterina Vylomova, Kevin Duh, and Chris Dyer, “Depth-Gated LSTM,” in arXiv.org, 2015.
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@inproceedings{10979491,
title = {Depth-Gated LSTM},
author = {{K. Yao} and {Trevor Cohn} and {Ekaterina Vylomova} and {Kevin Duh} and {Chris Dyer}},
year = 2015,
month = {8},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/a739ae988ba0e3ff232f4507627dfc282ba7b3f4},
}

A. Benton and M. Dredze, “Entity Linking for Spoken Language,” in Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Denver, Colorado, 2015, p. 225–230. doi:10.3115/v1/N15-1024
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@inproceedings{benton-dredze-2015-entity,
title = "Entity Linking for Spoken Language",
author = "Benton, Adrian and
Dredze, Mark",
editor = "Mihalcea, Rada and
Chai, Joyce and
Sarkar, Anoop",
booktitle = "Proceedings of the 2015 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies",
month = may # "{--}" # jun,
year = "2015",
address = "Denver, Colorado",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N15-1024",
doi = "10.3115/v1/N15-1024",
pages = "225--230",
}

Xiaodong Liu, Kevin Duh, and Yuji Matsumoto, “Multilingual Topic Models for Bilingual Dictionary Extraction,” in ACM Trans. Asian Low Resour. Lang. Inf. Process., 2015.
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@inproceedings{6095465,
title = {Multilingual Topic Models for Bilingual Dictionary Extraction},
author = {{Xiaodong Liu} and {Kevin Duh} and {Yuji Matsumoto}},
year = 2015,
month = {6},
booktitle = {ACM Trans. Asian Low Resour. Lang. Inf. Process.},
url = {https://www.semanticscholar.org/paper/acdd7809fe86f300d659792b27733601646fc860},
}

T. Wolfe, M. Dredze, and B. Van Durme, “Predicate Argument Alignment using a Global Coherence Model,” in Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Denver, Colorado, 2015, p. 11–20. doi:10.3115/v1/N15-1002
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@inproceedings{wolfe-etal-2015-predicate,
title = "Predicate Argument Alignment using a Global Coherence Model",
author = "Wolfe, Travis and
Dredze, Mark and
Van Durme, Benjamin",
editor = "Mihalcea, Rada and
Chai, Joyce and
Sarkar, Anoop",
booktitle = "Proceedings of the 2015 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies",
month = may # "{--}" # jun,
year = "2015",
address = "Denver, Colorado",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N15-1002",
doi = "10.3115/v1/N15-1002",
pages = "11--20",
}

M. Santillana, A. Nguyen, Mark Dredze, Michael J. Paul, E. Nsoesie, and J. Brownstein, “Combining Search, Social Media, and Traditional Data Sources to Improve Influenza Surveillance,” in PLoS Comput. Biol., 2015.
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@inproceedings{24689369,
title = {Combining Search, Social Media, and Traditional Data Sources to Improve Influenza Surveillance},
author = {{M. Santillana} and {A. Nguyen} and {Mark Dredze} and {Michael J. Paul} and {E. Nsoesie} and {J. Brownstein}},
year = 2015,
month = {8},
booktitle = {PLoS Comput. Biol.},
url = {https://www.semanticscholar.org/paper/84fed2a181f282fde8251882ea2a3f0b1e65bbe5},
}

Shiliang Wang, Michael J. Paul, and Mark Dredze, “Social Media as a Sensor of Air Quality and Public Response in China,” in Journal of Medical Internet Research, 2015.
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@inproceedings{18072917,
title = {Social Media as a Sensor of Air Quality and Public Response in China},
author = {{Shiliang Wang} and {Michael J. Paul} and {Mark Dredze}},
year = 2015,
month = {3},
booktitle = {Journal of Medical Internet Research},
url = {https://www.semanticscholar.org/paper/cc59eba7e3eab4eb95bb264a0db2496e4d19fcf7},
}

Tomas Figliolia, Thomas S. Murray, and A. Andreou, “Acoustic micro-Doppler signal processing with foveated electronic cochlea,” in Electronics Letters, 2015.
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@inproceedings{109863187,
title = {Acoustic micro-Doppler signal processing with foveated electronic cochlea},
author = {{Tomas Figliolia} and {Thomas S. Murray} and {A. Andreou}},
year = 2015,
month = {1},
booktitle = {Electronics Letters},
url = {https://www.semanticscholar.org/paper/9e4390846e21f4c4b40b8d2762bec31fd041fda5},
}

K. Strohbehn, R. C. Meitzler, A. Andreou, and R. E. Jenkins, “ANALOG IMAGE PROCESSING WITH SILICON RETINAS.” 2015.
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@inproceedings{9077931,
title = {ANALOG IMAGE PROCESSING WITH SILICON RETINAS},
author = {{K. Strohbehn} and {R. C. Meitzler} and {A. Andreou} and {R. E. Jenkins}},
year = 2015,
booktitle = {},
url = {https://www.semanticscholar.org/paper/c1e0ce486ae3e7a6ef02af3a341d16176ff8ebd6},
}

Michael J. Paul, Mark Dredze, David A. Broniatowski, and N. Generous, “Worldwide Influenza Surveillance through Twitter,” in AAAI Workshop: WWW and Public Health Intelligence, 2015.
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@inproceedings{17878129,
title = {Worldwide Influenza Surveillance through Twitter},
author = {{Michael J. Paul} and {Mark Dredze} and {David A. Broniatowski} and {N. Generous}},
year = 2015,
month = {4},
booktitle = {AAAI Workshop: WWW and Public Health Intelligence},
url = {https://www.semanticscholar.org/paper/37716db6dd12a67c74fc10d97011a1f59d7369be},
}

M. Yu, M. R. Gormley, and M. Dredze, “Combining Word Embeddings and Feature Embeddings for Fine-grained Relation Extraction,” in Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Denver, Colorado, 2015, p. 1374–1379. doi:10.3115/v1/N15-1155
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@inproceedings{yu-etal-2015-combining,
title = "Combining Word Embeddings and Feature Embeddings for Fine-grained Relation Extraction",
author = "Yu, Mo and
Gormley, Matthew R. and
Dredze, Mark",
editor = "Mihalcea, Rada and
Chai, Joyce and
Sarkar, Anoop",
booktitle = "Proceedings of the 2015 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies",
month = may # "{--}" # jun,
year = "2015",
address = "Denver, Colorado",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N15-1155",
doi = "10.3115/v1/N15-1155",
pages = "1374--1379",
}

David J. McIver, David A. Broniatowski, Mark Dredze, Michael J. Paul, and A. Dugas, “Using Social Media to Perform Local Influenza Surveillance in an Inner-City Hospital: A Retrospective Observational Study,” in JMIR Public Health and Surveillance, 2015.
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@inproceedings{11266353,
title = {Using Social Media to Perform Local Influenza Surveillance in an Inner-City Hospital: A Retrospective Observational Study},
author = {{David J. McIver} and {David A. Broniatowski} and {Mark Dredze} and {Michael J. Paul} and {A. Dugas}},
year = 2015,
month = {5},
booktitle = {JMIR Public Health and Surveillance},
url = {https://www.semanticscholar.org/paper/f14550978577dd782709130600347f1b3d3db11d},
}

Deyi Xiong, Kevin Duh, Christian Hardmeier, and Roberto Navigli, “Proceedings of the 1st Workshop on Semantics-Driven Statistical Machine Translation (S2MT 2015).” 2015.
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@inproceedings{60903386,
title = {Proceedings of the 1st Workshop on Semantics-Driven Statistical Machine Translation (S2MT 2015)},
author = {{Deyi Xiong} and {Kevin Duh} and {Christian Hardmeier} and {Roberto Navigli}},
year = 2015,
booktitle = {},
url = {https://www.semanticscholar.org/paper/adbe183b8e35779e7abff33ca85461c296155cd0},
}

H. He, H. Daumé III, and J. Eisner, “Learning to Search in Branch-and-Bound Algorithms,” in Advances in Neural Information Processing Systems 27 (NeurIPS), Montreal, 2014, p. 3293–3301.
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@InProceedings{he-daume-eisner-2014,
author = "He He and Hal {Daum\'{e} III} and Jason Eisner",
title = "Learning to Search in Branch-and-Bound Algorithms",
booktitle = "Advances in Neural Information Processing Systems 27
(NeurIPS)",
pages = "3293--3301",
year = "2014",
month = dec,
address = "Montreal",
URL = "http://cs.jhu.edu/~jason/papers/#he-daume-eisner-2014",
}

J. Hong and J. Eisner, “Deriving Multi-Headed Projective Dependency Parses from Link Grammar Parses,” in 13th International Workshop on Treebanks and Linguistic Theories (TLT), Tübingen, 2014.
[BibTeX] [Link]

@InProceedings{hong-eisner-2014,
author = "Juneki Hong and Jason Eisner",
title = "Deriving Multi-Headed Projective Dependency Parses
from Link Grammar Parses",
booktitle = "13th International Workshop on Treebanks and
Linguistic Theories (TLT)",
note = "5 pages plus appendices",
year = "2014",
month = dec,
address = "T{\"u}bingen",
URL = "http://cs.jhu.edu/~jason/papers/#hong-eisner-2014",
}

Byron C. Wallace, Michael J. Paul, U. Sarkar, T. Trikalinos, and Mark Dredze, “A large-scale quantitative analysis of latent factors and sentiment in online doctor reviews,” in J. Am. Medical Informatics Assoc., 2014.
[BibTeX] [Link]

@inproceedings{11927210,
title = {A large-scale quantitative analysis of latent factors and sentiment in online doctor reviews},
author = {{Byron C. Wallace} and {Michael J. Paul} and {U. Sarkar} and {T. Trikalinos} and {Mark Dredze}},
year = 2014,
month = {11},
booktitle = {J. Am. Medical Informatics Assoc.},
url = {https://www.semanticscholar.org/paper/4697d14f9c3ded5182fc8051f62b8ab0c315ac8c},
}

M. Di Federico, P. Julián, A. Andreou, and P. Mandolesi, “Fully functional fine-grain vertically integrated 3D focal plane neuromorphic processor,” in IEEE SOI-3D-Subthreshold Microelectronics Technology Unified Conference, 2014.
[BibTeX] [Link]

@inproceedings{40134619,
title = {Fully functional fine-grain vertically integrated 3D focal plane neuromorphic processor},
author = {{M. Di Federico} and {P. Julián} and {A. Andreou} and {P. Mandolesi}},
year = 2014,
month = {10},
booktitle = {IEEE SOI-3D-Subthreshold Microelectronics Technology Unified Conference},
url = {https://www.semanticscholar.org/paper/ac4535e5ac8a7a622bde497f64249d6f5e24ebdc},
}

Michael J. Paul, Mark Dredze, and David A. Broniatowski, “Twitter Improves Influenza Forecasting,” in PLOS Currents, 2014.
[BibTeX] [Link]

@inproceedings{4816342,
title = {Twitter Improves Influenza Forecasting},
author = {{Michael J. Paul} and {Mark Dredze} and {David A. Broniatowski}},
year = 2014,
month = {10},
booktitle = {PLOS Currents},
url = {https://www.semanticscholar.org/paper/1a65756a1c9641fdd7dbee5f7b46e72fb40ca772},
}

Joy L. Lee, M. Decamp, Mark Dredze, M. Chisolm, and Z. Berger, “What Are Health-Related Users Tweeting? A Qualitative Content Analysis of Health-Related Users and Their Messages on Twitter,” in Journal of Medical Internet Research, 2014.
[BibTeX] [Link]

@inproceedings{20229016,
title = {What Are Health-Related Users Tweeting? A Qualitative Content Analysis of Health-Related Users and Their Messages on Twitter},
author = {{Joy L. Lee} and {M. Decamp} and {Mark Dredze} and {M. Chisolm} and {Z. Berger}},
year = 2014,
month = {10},
booktitle = {Journal of Medical Internet Research},
url = {https://www.semanticscholar.org/paper/78de8021f889aa36ad38f128cbb90cc91c84db0c},
}

G. Coppersmith, M. Dredze, and C. Harman, “Quantifying Mental Health Signals in Twitter,” in Proceedings of the Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality, Baltimore, Maryland, USA, 2014, p. 51–60. doi:10.3115/v1/W14-3207
[BibTeX] [Link]

@inproceedings{coppersmith-etal-2014-quantifying,
title = "Quantifying Mental Health Signals in {T}witter",
author = "Coppersmith, Glen and
Dredze, Mark and
Harman, Craig",
editor = "Resnik, Philip and
Resnik, Rebecca and
Mitchell, Margaret",
booktitle = "Proceedings of the Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality",
month = jun,
year = "2014",
address = "Baltimore, Maryland, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W14-3207",
doi = "10.3115/v1/W14-3207",
pages = "51--60",
}

M. R. Gormley, M. Mitchell, B. Van Durme, and M. Dredze, “Low-Resource Semantic Role Labeling,” in Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Baltimore, Maryland, 2014, p. 1177–1187. doi:10.3115/v1/P14-1111
[BibTeX] [Link]

@inproceedings{gormley-etal-2014-low,
title = "Low-Resource Semantic Role Labeling",
author = "Gormley, Matthew R. and
Mitchell, Margaret and
Van Durme, Benjamin and
Dredze, Mark",
editor = "Toutanova, Kristina and
Wu, Hua",
booktitle = "Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = jun,
year = "2014",
address = "Baltimore, Maryland",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P14-1111",
doi = "10.3115/v1/P14-1111",
pages = "1177--1187",
}

N. Andrews, J. Eisner, and M. Dredze, “Robust Entity Clustering via Phylogenetic Inference,” in Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Baltimore, Maryland, 2014, p. 775–785. doi:10.3115/v1/P14-1073
[BibTeX] [Link]

@inproceedings{andrews-etal-2014-robust,
title = "Robust Entity Clustering via Phylogenetic Inference",
author = "Andrews, Nicholas and
Eisner, Jason and
Dredze, Mark",
editor = "Toutanova, Kristina and
Wu, Hua",
booktitle = "Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = jun,
year = "2014",
address = "Baltimore, Maryland",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P14-1073",
doi = "10.3115/v1/P14-1073",
pages = "775--785",
}

N. Peng, Y. Wang, and M. Dredze, “Learning Polylingual Topic Models from Code-Switched Social Media Documents,” in Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), Baltimore, Maryland, 2014, p. 674–679. doi:10.3115/v1/P14-2110
[BibTeX] [Link]

@inproceedings{peng-etal-2014-learning,
title = "Learning Polylingual Topic Models from Code-Switched Social Media Documents",
author = "Peng, Nanyun and
Wang, Yiming and
Dredze, Mark",
editor = "Toutanova, Kristina and
Wu, Hua",
booktitle = "Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)",
month = jun,
year = "2014",
address = "Baltimore, Maryland",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P14-2110",
doi = "10.3115/v1/P14-2110",
pages = "674--679",
}

M. Yu and M. Dredze, “Improving Lexical Embeddings with Semantic Knowledge,” in Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), Baltimore, Maryland, 2014, p. 545–550. doi:10.3115/v1/P14-2089
[BibTeX] [Link]

@inproceedings{yu-dredze-2014-improving,
title = "Improving Lexical Embeddings with Semantic Knowledge",
author = "Yu, Mo and
Dredze, Mark",
editor = "Toutanova, Kristina and
Wu, Hua",
booktitle = "Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)",
month = jun,
year = "2014",
address = "Baltimore, Maryland",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P14-2089",
doi = "10.3115/v1/P14-2089",
pages = "545--550",
}

N. Andrews, J. Eisner, and M. Dredze, “Robust Entity Clustering via Phylogenetic Inference,” in Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (ACL), Baltimore, 2014, p. 775–785. doi:10.3115/v1/P14-1073
[BibTeX] [Link]

@InProceedings{andrews-eisner-dredze-2014,
aclid = "P14-1073",
doi = "10.3115/v1/P14-1073",
author = "Nicholas Andrews and Jason Eisner and Mark Dredze",
title = "Robust Entity Clustering via Phylogenetic Inference",
booktitle = "Proceedings of the 52nd Annual Meeting of the
Association for Computational Linguistics (ACL)",
pages = "775--785",
year = "2014",
month = jun,
address = "Baltimore",
URL = "http://cs.jhu.edu/~jason/papers/#andrews-eisner-dredze-2014",
}

R. Cotterell, N. Peng, and J. Eisner, “Stochastic Contextual Edit Distance and Probabilistic FSTs,” in Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), Baltimore, 2014, p. 625–630. doi:10.3115/v1/P14-2102
[BibTeX] [Link]

@InProceedings{cotterell-peng-eisner-2014,
aclid = "P14-2102",
doi = "10.3115/v1/P14-2102",
author = "Ryan Cotterell and Nanyun Peng and Jason Eisner",
title = "Stochastic Contextual Edit Distance and Probabilistic
{FST}s",
booktitle = "Proceedings of the 52nd Annual Meeting of the
Association for Computational Linguistics (Volume 2:
Short Papers)",
pages = "625--630",
year = "2014",
month = jun,
address = "Baltimore",
URL = "http://cs.jhu.edu/~jason/papers/#cotterell-peng-eisner-2014",
}

Mark Dredze, Renyuan Cheng, Michael J. Paul, and David A. Broniatowski, “HealthTweets.org: A Platform for Public Health Surveillance Using Twitter,” in AAAI Conference on Artificial Intelligence, 2014.
[BibTeX] [Link]

@inproceedings{61657545,
title = {HealthTweets.org: A Platform for Public Health Surveillance Using Twitter},
author = {{Mark Dredze} and {Renyuan Cheng} and {Michael J. Paul} and {David A. Broniatowski}},
year = 2014,
month = {6},
booktitle = {AAAI Conference on Artificial Intelligence},
url = {https://www.semanticscholar.org/paper/3f83f06576ebfbee3978e6ad4a0a4cdc505f1753},
}

Denham, L. I. Winkler, Tamás Bohm, A. Bendixen, A. Andreou, Julio Georgiou, Guillaume Garreau, Botond Hajdu, and L. Susan, “Demonstration #9: Synchrony test (out of phase).” 2014.
[BibTeX] [Link]

@inproceedings{186737415,
title = {Demonstration #9: Synchrony test (out of phase)},
author = {{Denham} and {L. I. Winkler} and {Tamás Bohm} and {A. Bendixen} and {A. Andreou} and {Julio Georgiou} and {Guillaume Garreau} and {Botond Hajdu} and {L. Susan}},
year = 2014,
booktitle = {},
url = {https://www.semanticscholar.org/paper/3901b8342371370b47ae994c9729ab3ae104a784},
}

Denham, L. I. Winkler, Tamás Bohm, A. Bendixen, A. Andreou, Julio Georgiou, Guillaume Garreau, Botond Hajdu, and L. Susan, “Demonstration #1: 1 ball standing (1Hz).” 2014.
[BibTeX] [Link]

@inproceedings{188651514,
title = {Demonstration #1: 1 ball standing (1Hz)},
author = {{Denham} and {L. I. Winkler} and {Tamás Bohm} and {A. Bendixen} and {A. Andreou} and {Julio Georgiou} and {Guillaume Garreau} and {Botond Hajdu} and {L. Susan}},
year = 2014,
booktitle = {},
url = {https://www.semanticscholar.org/paper/95ee2c21760910387899f99c8db5bc64439685b7},
}

L. Shestopalova, Tamás Bohm, A. Bendixen, A. Andreou, Julio Georgiou, Guillaume Garreau, Botond Hajdu, S. Denham, and I. Winkler, “Demonstration #6: 2 balls moving (2.67Hz).” 2014.
[BibTeX] [Link]

@inproceedings{125906262,
title = {Demonstration #6: 2 balls moving (2.67Hz)},
author = {{L. Shestopalova} and {Tamás Bohm} and {A. Bendixen} and {A. Andreou} and {Julio Georgiou} and {Guillaume Garreau} and {Botond Hajdu} and {S. Denham} and {I. Winkler}},
year = 2014,
booktitle = {},
url = {https://www.semanticscholar.org/paper/55cd72ac42a28fea8f5e58ce66dc72439d0d88a4},
}

David A. Broniatowski, Michael J. Paul, and Mark Dredze, “Twitter: big data opportunities.,” in Science, 2014.
[BibTeX] [Link]

@inproceedings{45778614,
title = {Twitter: big data opportunities.},
author = {{David A. Broniatowski} and {Michael J. Paul} and {Mark Dredze}},
year = 2014,
month = {7},
booktitle = {Science},
url = {https://www.semanticscholar.org/paper/484589552d3941f25f9e722c4268784aa1b5d465},
}

Mark Dredze and Michael J. Paul, “Natural Language Processing for Health and Social Media.” 2014.
[BibTeX] [Link]

@inproceedings{17398392,
title = {Natural Language Processing for Health and Social Media},
author = {{Mark Dredze} and {Michael J. Paul}},
year = 2014,
booktitle = {},
url = {https://www.semanticscholar.org/paper/a6dd47b4c1945b8e10c4d1e72f1dbb29ed35ab03},
}

J. Ayers, B. Althouse, and Mark Dredze, “Could behavioral medicine lead the web data revolution?,” in Journal of the American Medical Association (JAMA), 2014.
[BibTeX] [Link]

@inproceedings{205055790,
title = {Could behavioral medicine lead the web data revolution?},
author = {{J. Ayers} and {B. Althouse} and {Mark Dredze}},
year = 2014,
month = {4},
booktitle = {Journal of the American Medical Association (JAMA)},
url = {https://www.semanticscholar.org/paper/1f54cf05afa62ce9f959746b86a1dfffa45cf32b},
}

L. Shestopalova, Tamás Bohm, A. Bendixen, A. Andreou, Julio Georgiou, Guillaume Garreau, Botond Hajdu, S. Denham, and I. Winkler, “Stimulus: Incongruent/Moving/Joint.” 2014.
[BibTeX] [Link]

@inproceedings{146311108,
title = {Stimulus: Incongruent/Moving/Joint},
author = {{L. Shestopalova} and {Tamás Bohm} and {A. Bendixen} and {A. Andreou} and {Julio Georgiou} and {Guillaume Garreau} and {Botond Hajdu} and {S. Denham} and {I. Winkler}},
year = 2014,
month = {3},
booktitle = {},
url = {https://www.semanticscholar.org/paper/83cf2445bf234b520b03dd7e47ea9282bc6512aa},
}

A. Abbasi, D. Adjeroh, Mark Dredze, Michael J. Paul, F. Zahedi, Huimin Zhao, N. Walia, H. Jain, Patrick Sanvanson, R. Shaker, Marco D. Huesch, Richard Beal, W. Zheng, M. Abate, and Arun Ross, “Social Media Analytics for Smart Health,” in IEEE Intelligent Systems, 2014.
[BibTeX] [Link]

@inproceedings{206468861,
title = {Social Media Analytics for Smart Health},
author = {{A. Abbasi} and {D. Adjeroh} and {Mark Dredze} and {Michael J. Paul} and {F. Zahedi} and {Huimin Zhao} and {N. Walia} and {H. Jain} and {Patrick Sanvanson} and {R. Shaker} and {Marco D. Huesch} and {Richard Beal} and {W. Zheng} and {M. Abate} and {Arun Ross}},
year = 2014,
month = {3},
booktitle = {IEEE Intelligent Systems},
url = {https://www.semanticscholar.org/paper/49caf06456ca595330040bfba38c22421c50c0d5},
}

Thomas J. Dawidczyk, Josué F Martínez Hardigree, G. Johns, R. Ozgun, Olivia Alley, A. Andreou, N. Marković, and H. Katz, “Visualizing and quantifying charge distributions correlated to threshold voltage shifts in lateral organic transistors.,” in ACS Nano, 2014.
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@inproceedings{27671912,
title = {Visualizing and quantifying charge distributions correlated to threshold voltage shifts in lateral organic transistors.},
author = {{Thomas J. Dawidczyk} and {Josué F Martínez Hardigree} and {G. Johns} and {R. Ozgun} and {Olivia Alley} and {A. Andreou} and {N. Marković} and {H. Katz}},
year = 2014,
month = {2},
booktitle = {ACS Nano},
url = {https://www.semanticscholar.org/paper/38222721fd352cfa963ad362ab9cf8b0b2af03a6},
}

M. Osborne and Mark Dredze, “Facebook, Twitter and Google Plus for Breaking News: Is There a Winner?,” in International Conference on Web and Social Media, 2014.
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@inproceedings{31566441,
title = {Facebook, Twitter and Google Plus for Breaking News: Is There a Winner?},
author = {{M. Osborne} and {Mark Dredze}},
year = 2014,
month = {5},
booktitle = {International Conference on Web and Social Media},
url = {https://www.semanticscholar.org/paper/6c78a1358f38995462c7358d1679b817edf88b6c},
}

L. Shestopalova, Tamás Bohm, A. Bendixen, A. Andreou, J. Georgiou, Guillaume Garreau, Botond Hajdu, S. Denham, and I. Winkler, “Do audio-visual motion cues promote segregation of auditory streams?,” in Frontiers in Neuroscience, 2014.
[BibTeX] [Link]

@inproceedings{640769,
title = {Do audio-visual motion cues promote segregation of auditory streams?},
author = {{L. Shestopalova} and {Tamás Bohm} and {A. Bendixen} and {A. Andreou} and {J. Georgiou} and {Guillaume Garreau} and {Botond Hajdu} and {S. Denham} and {I. Winkler}},
year = 2014,
month = {4},
booktitle = {Frontiers in Neuroscience},
url = {https://www.semanticscholar.org/paper/378b134a47091a44dccb8e886b63be78b33f644e},
}

B. Althouse, Jon-Patrick Allem, Matthew A. Childers, Mark Dredze, and J. Ayers, “Population health concerns during the United States’ Great Recession.,” in American Journal of Preventive Medicine, 2014.
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@inproceedings{20264828,
title = {Population health concerns during the United States' Great Recession.},
author = {{B. Althouse} and {Jon-Patrick Allem} and {Matthew A. Childers} and {Mark Dredze} and {J. Ayers}},
year = 2014,
month = {2},
booktitle = {American Journal of Preventive Medicine},
url = {https://www.semanticscholar.org/paper/1c89fa07ada14df5d5388642d173c8e805f7388f},
}

Shiliang Wang, Michael J. Paul, and Mark Dredze, “Exploring Health Topics in Chinese Social Media: An Analysis of Sina Weibo,” in AAAI Conference on Artificial Intelligence, 2014.
[BibTeX] [Link]

@inproceedings{8870697,
title = {Exploring Health Topics in Chinese Social Media: An Analysis of Sina Weibo},
author = {{Shiliang Wang} and {Michael J. Paul} and {Mark Dredze}},
year = 2014,
month = {6},
booktitle = {AAAI Conference on Artificial Intelligence},
url = {https://www.semanticscholar.org/paper/46a0f4c55951a2be5a8f220414ba660e6aba49a3},
}

J. Ayers, B. Althouse, Morgan Johnson, Mark Dredze, and Joanna E. Cohen, “What’s the healthiest day?: Circaseptan (weekly) rhythms in healthy considerations.,” in American Journal of Preventive Medicine, 2014.
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@inproceedings{22399217,
title = {What's the healthiest day?: Circaseptan (weekly) rhythms in healthy considerations.},
author = {{J. Ayers} and {B. Althouse} and {Morgan Johnson} and {Mark Dredze} and {Joanna E. Cohen}},
year = 2014,
month = {7},
booktitle = {American Journal of Preventive Medicine},
url = {https://www.semanticscholar.org/paper/13ae9734f3924e419832b6e474001e62a1efbcd2},
}

Glen A. Coppersmith, Craig Harman, and Mark Dredze, “Measuring Post Traumatic Stress Disorder in Twitter,” in International Conference on Web and Social Media, 2014.
[BibTeX] [Link]

@inproceedings{14612598,
title = {Measuring Post Traumatic Stress Disorder in Twitter},
author = {{Glen A. Coppersmith} and {Craig Harman} and {Mark Dredze}},
year = 2014,
month = {5},
booktitle = {International Conference on Web and Social Media},
url = {https://www.semanticscholar.org/paper/ea24d85e059d7d1dc201bd0380c76caf1f78f1e4},
}

Adrian Benton, Jay DeYoung, Adam R. Teichert, Stephen Mayhew, Mark Dredze, Benjamin Van Durme, and Max Thomas, “Faster ( and Better ) Entity Linking with Cascades.” 2014.
[BibTeX] [Link]

@inproceedings{15885284,
title = {Faster ( and Better ) Entity Linking with Cascades},
author = {{Adrian Benton} and {Jay DeYoung} and {Adam R. Teichert} and {Stephen Mayhew} and {Mark Dredze} and {Benjamin Van Durme} and {Max Thomas}},
year = 2014,
booktitle = {},
url = {https://www.semanticscholar.org/paper/04cc3e2947f6183d4ae6959be13544ebd799a8f0},
}

Michael J. Paul and Mark Dredze, “Discovering Health Topics in Social Media Using Topic Models,” in PLoS ONE, 2014.
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@inproceedings{5868280,
title = {Discovering Health Topics in Social Media Using Topic Models},
author = {{Michael J. Paul} and {Mark Dredze}},
year = 2014,
month = {8},
booktitle = {PLoS ONE},
url = {https://www.semanticscholar.org/paper/07f07fb7c5993029222ffa21619f226a4feb2e76},
}

Denham, L. I. Winkler, Tamás Bohm, A. Bendixen, A. Andreou, Julio Georgiou, Guillaume Garreau, Botond Hajdu, and L. Susan, “Demonstration #5: 2 balls standing (8Hz).” 2014.
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@inproceedings{126421038,
title = {Demonstration #5: 2 balls standing (8Hz)},
author = {{Denham} and {L. I. Winkler} and {Tamás Bohm} and {A. Bendixen} and {A. Andreou} and {Julio Georgiou} and {Guillaume Garreau} and {Botond Hajdu} and {L. Susan}},
year = 2014,
booktitle = {},
url = {https://www.semanticscholar.org/paper/e27ef3733d7881876f91646e14cb4f3d9aadf8fc},
}

David A. Broniatowski, Michael J. Paul, and Mark Dredze, “National and Local Influenza Surveillance through Twitter: An Analysis of the 2012-2013 Influenza Epidemic,” in PLoS ONE, 2013.
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@inproceedings{2346247,
title = {National and Local Influenza Surveillance through Twitter: An Analysis of the 2012-2013 Influenza Epidemic},
author = {{David A. Broniatowski} and {Michael J. Paul} and {Mark Dredze}},
year = 2013,
month = {12},
booktitle = {PLoS ONE},
url = {https://www.semanticscholar.org/paper/687a6a77fcfe143198c311f734a0d68e00943ceb},
}

H. He, H. Daumé III, and J. Eisner, “Dynamic Feature Selection for Dependency Parsing,” in Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Seattle, 2013, p. 1455–1464.
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@InProceedings{he-daume-eisner-2013,
aclid = "D13-1152",
author = "He He and Hal {Daum\'{e} III} and Jason Eisner",
title = "Dynamic Feature Selection for Dependency Parsing",
booktitle = "Proceedings of the Conference on Empirical Methods in
Natural Language Processing (EMNLP)",
pages = "1455--1464",
year = "2013",
month = oct,
address = "Seattle",
URL = "http://cs.jhu.edu/~jason/papers/#he-daume-eisner-2013",
}

T. Wolfe, B. Van Durme, M. Dredze, N. Andrews, C. Beller, C. Callison-Burch, J. DeYoung, J. Snyder, J. Weese, T. Xu, and X. Yao, “PARMA: A Predicate Argument Aligner,” in Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), Sofia, Bulgaria, 2013, p. 63–68.
[BibTeX] [Link]

@inproceedings{wolfe-etal-2013-parma,
title = "{PARMA}: A Predicate Argument Aligner",
author = "Wolfe, Travis and
Van Durme, Benjamin and
Dredze, Mark and
Andrews, Nicholas and
Beller, Charley and
Callison-Burch, Chris and
DeYoung, Jay and
Snyder, Justin and
Weese, Jonathan and
Xu, Tan and
Yao, Xuchen",
editor = "Schuetze, Hinrich and
Fung, Pascale and
Poesio, Massimo",
booktitle = "Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)",
month = aug,
year = "2013",
address = "Sofia, Bulgaria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P13-2012",
pages = "63--68",
}

F. Ferraro and J. Eisner, “A Virtual Manipulative for Learning Log-Linear Models,” in Proceedings of the Fourth Workshop on Teaching NLP and CL, Sofia, Bulgaria, 2013, p. 66–76.
[BibTeX] [Link]

@InProceedings{ferraro-eisner-2013,
aclid = "W13-3411",
author = "Francis Ferraro and Jason Eisner",
title = "A Virtual Manipulative for Learning Log-Linear
Models",
booktitle = "Proceedings of the Fourth Workshop on Teaching NLP and
CL",
pages = "66--76",
year = "2013",
month = aug,
address = "Sofia, Bulgaria",
URL = "http://cs.jhu.edu/~jason/papers/#ferraro-eisner-2013",
}

P. Littell, L. Levin, J. Eisner, and D. Radev, “Introducing Computational Concepts in a Linguistics Olympiad,” in Proceedings of the Fourth Workshop on Teaching NLP and CL, Sofia, Bulgaria, 2013, p. 18–26.
[BibTeX] [Link]

@InProceedings{littell-et-al-2013,
aclid = "W13-3403",
author = "Patrick Littell and Lori Levin and Jason Eisner and
Dragomir Radev",
title = "Introducing Computational Concepts in a Linguistics
Olympiad",
booktitle = "Proceedings of the Fourth Workshop on Teaching NLP and
CL",
pages = "18--26",
year = "2013",
month = aug,
address = "Sofia, Bulgaria",
URL = "http://cs.jhu.edu/~jason/papers/#littell-et-al-2013",
}

M. Gormley and J. Eisner, “Nonconvex Global Optimization for Latent-Variable Models,” in Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL), Sofia, Bulgaria, 2013, p. 444–454.
[BibTeX] [Link]

@InProceedings{gormley-eisner-2013,
aclid = "P13-1044",
author = "Matthew Gormley and Jason Eisner",
title = "Nonconvex Global Optimization for Latent-Variable
Models",
booktitle = "Proceedings of the 51st Annual Meeting of the
Association for Computational Linguistics (ACL)",
pages = "444--454",
year = "2013",
month = aug,
address = "Sofia, Bulgaria",
URL = "http://cs.jhu.edu/~jason/papers/#gormley-eisner-2013",
}

M. J. Paul and M. Dredze, “Drug Extraction from the Web: Summarizing Drug Experiences with Multi-Dimensional Topic Models,” in Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Atlanta, Georgia, 2013, p. 168–178.
[BibTeX] [Link]

@inproceedings{paul-dredze-2013-drug,
title = "Drug Extraction from the Web: Summarizing Drug Experiences with Multi-Dimensional Topic Models",
author = "Paul, Michael J. and
Dredze, Mark",
editor = "Vanderwende, Lucy and
Daum{\'e} III, Hal and
Kirchhoff, Katrin",
booktitle = "Proceedings of the 2013 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies",
month = jun,
year = "2013",
address = "Atlanta, Georgia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N13-1017",
pages = "168--178",
}

A. Lamb, M. J. Paul, and M. Dredze, “Separating Fact from Fear: Tracking Flu Infections on Twitter,” in Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Atlanta, Georgia, 2013, p. 789–795.
[BibTeX] [Link]

@inproceedings{lamb-etal-2013-separating,
title = "Separating Fact from Fear: Tracking Flu Infections on {T}witter",
author = "Lamb, Alex and
Paul, Michael J. and
Dredze, Mark",
editor = "Vanderwende, Lucy and
Daum{\'e} III, Hal and
Kirchhoff, Katrin",
booktitle = "Proceedings of the 2013 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies",
month = jun,
year = "2013",
address = "Atlanta, Georgia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N13-1097",
pages = "789--795",
}

S. Bergsma, M. Dredze, B. Van Durme, T. Wilson, and D. Yarowsky, “Broadly Improving User Classification via Communication-Based Name and Location Clustering on Twitter,” in Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Atlanta, Georgia, 2013, p. 1010–1019.
[BibTeX] [Link]

@inproceedings{bergsma-etal-2013-broadly,
title = "Broadly Improving User Classification via Communication-Based Name and Location Clustering on {T}witter",
author = "Bergsma, Shane and
Dredze, Mark and
Van Durme, Benjamin and
Wilson, Theresa and
Yarowsky, David",
editor = "Vanderwende, Lucy and
Daum{\'e} III, Hal and
Kirchhoff, Katrin",
booktitle = "Proceedings of the 2013 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies",
month = jun,
year = "2013",
address = "Atlanta, Georgia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N13-1121",
pages = "1010--1019",
}

J. Snyder, R. Knowles, M. Dredze, M. Gormley, and T. Wolfe, “Topic Models and Metadata for Visualizing Text Corpora,” in Proceedings of the 2013 NAACL HLT Demonstration Session, Atlanta, Georgia, 2013, p. 5–9.
[BibTeX] [Link]

@inproceedings{snyder-etal-2013-topic,
title = "Topic Models and Metadata for Visualizing Text Corpora",
author = "Snyder, Justin and
Knowles, Rebecca and
Dredze, Mark and
Gormley, Matthew and
Wolfe, Travis",
editor = "Dyer, Chris and
Higgins, Derrick",
booktitle = "Proceedings of the 2013 {NAACL} {HLT} Demonstration Session",
month = jun,
year = "2013",
address = "Atlanta, Georgia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N13-3002",
pages = "5--9",
}

M. Joshi, M. Dredze, W. W. Cohen, and C. P. Rosé, “What’s in a Domain? Multi-Domain Learning for Multi-Attribute Data,” in Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Atlanta, Georgia, 2013, p. 685–690.
[BibTeX] [Link]

@inproceedings{joshi-etal-2013-whats,
title = "What{'}s in a Domain? Multi-Domain Learning for Multi-Attribute Data",
author = "Joshi, Mahesh and
Dredze, Mark and
Cohen, William W. and
Ros{\'e}, Carolyn P.",
editor = "Vanderwende, Lucy and
Daum{\'e} III, Hal and
Kirchhoff, Katrin",
booktitle = "Proceedings of the 2013 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies",
month = jun,
year = "2013",
address = "Atlanta, Georgia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N13-1080",
pages = "685--690",
}

J. Jiang, T. Moon, H. Daumé III, and J. Eisner, “Prioritized Asynchronous Belief Propagation,” in ICML Workshop on Inferning: Interactions between Inference and Learning, Atlanta, 2013.
[BibTeX] [Link]

@InProceedings{jiang-et-al-2013,
author = "Jiarong Jiang and Taesun Moon and Hal {Daum\'{e} III}
and Jason Eisner",
title = "Prioritized Asynchronous Belief Propagation",
booktitle = "ICML Workshop on Inferning: Interactions between
Inference and Learning",
note = "5 pages",
year = "2013",
month = jun,
address = "Atlanta",
URL = "http://cs.jhu.edu/~jason/papers/#jiang-et-al-2013",
}

Tamás Bohm, L. Shestopalova, A. Bendixen, A. Andreou, J. Georgiou, Guillaume Garreau, P. Pouliquen, A. Cassidy, S. Denham, and I. Winkler, “The role of perceived source location in auditory stream segregation: Separation affects sound organization, common fate does not,” in Learning & Perception, 2013.
[BibTeX] [Link]

@inproceedings{54210602,
title = {The role of perceived source location in auditory stream segregation: Separation affects sound organization, common fate does not},
author = {{Tamás Bohm} and {L. Shestopalova} and {A. Bendixen} and {A. Andreou} and {J. Georgiou} and {Guillaume Garreau} and {P. Pouliquen} and {A. Cassidy} and {S. Denham} and {I. Winkler}},
year = 2013,
month = {6},
booktitle = {Learning & Perception},
url = {https://www.semanticscholar.org/paper/d085354dfe17f80bdd52435896c63faf019641ff},
}

F. Morabito, A. Andreou, and E. Chicca, “Neuromorphic Engineering: From Neural Systems to Brain-Like Engineered Systems,” in Neural Networks, 2013.
[BibTeX] [Link]

@inproceedings{8535893,
title = {Neuromorphic Engineering: From Neural Systems to Brain-Like Engineered Systems},
author = {{F. Morabito} and {A. Andreou} and {E. Chicca}},
year = 2013,
month = {9},
booktitle = {Neural Networks},
url = {https://www.semanticscholar.org/paper/3264cbe12b2305543a7c1c14c61d509d3c945fa6},
}

A. Cassidy, J. Georgiou, and A. Andreou, “Design of silicon brains in the nano-CMOS era: Spiking neurons, learning synapses and neural architecture optimization,” in Neural Networks, 2013.
[BibTeX] [Link]

@inproceedings{7701315,
title = {Design of silicon brains in the nano-CMOS era: Spiking neurons, learning synapses and neural architecture optimization},
author = {{A. Cassidy} and {J. Georgiou} and {A. Andreou}},
year = 2013,
month = {9},
booktitle = {Neural Networks},
url = {https://www.semanticscholar.org/paper/4ad2573355f5f957faaf792153aa782254cbb31d},
}

R. Ozgun, H. Katz, and A. Andreou, “Organic diode implementations in configurable architectures and temperature sensors,” in 2013 Microsystems for Measurement and Instrumentation: Fulfilling the Promise (MAMNA), 2013.
[BibTeX] [Link]

@inproceedings{30083992,
title = {Organic diode implementations in configurable architectures and temperature sensors},
author = {{R. Ozgun} and {H. Katz} and {A. Andreou}},
year = 2013,
month = {5},
booktitle = {2013 Microsystems for Measurement and Instrumentation: Fulfilling the Promise (MAMNA)},
url = {https://www.semanticscholar.org/paper/8c99056b72e9c431450ac04b3629b12495d81da0},
}

Sudarshan Ramenahalli, Daniel R. Mendat, S. Dura-Bernal, E. Culurciello, E. Niebur, and A. Andreou, “Audio-visual saliency map: Overview, basic models and hardware implementation,” in Annual Conference on Information Sciences and Systems, 2013.
[BibTeX] [Link]

@inproceedings{17242638,
title = {Audio-visual saliency map: Overview, basic models and hardware implementation},
author = {{Sudarshan Ramenahalli} and {Daniel R. Mendat} and {S. Dura-Bernal} and {E. Culurciello} and {E. Niebur} and {A. Andreou}},
year = 2013,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/ef483498459b9fbb64b24b807ce3743535d919d1},
}

Mark Dredze, Michael J. Paul, S. Bergsma, and Hieu V. Tran, “Carmen: A Twitter Geolocation System with Applications to Public Health.” 2013.
[BibTeX] [Link]

@inproceedings{17988849,
title = {Carmen: A Twitter Geolocation System with Applications to Public Health},
author = {{Mark Dredze} and {Michael J. Paul} and {S. Bergsma} and {Hieu V. Tran}},
year = 2013,
booktitle = {},
url = {https://www.semanticscholar.org/paper/9bc46fb12f2c7fae0e9e56e734e6efb9ca07fd98},
}

Thomas S. Murray, P. Pouliquen, and A. Andreou, “Design of a Parallel Sampling Encoder for Analog to Information (A2I) Converters: Theory, Architecture and.” 2013.
[BibTeX] [Link]

@inproceedings{12931494,
title = {Design of a Parallel Sampling Encoder for Analog to Information (A2I) Converters: Theory, Architecture and},
author = {{Thomas S. Murray} and {P. Pouliquen} and {A. Andreou}},
year = 2013,
month = {3},
booktitle = {},
url = {https://www.semanticscholar.org/paper/03c0a941a1364d59e94c550375222e61fcb1cd8d},
}

Michael J. Paul, Byron C. Wallace, and Mark Dredze, “What Affects Patient (Dis)satisfaction? Analyzing Online Doctor Ratings with a Joint Topic-Sentiment Model,” in AAAI Conference on Artificial Intelligence, 2013.
[BibTeX] [Link]

@inproceedings{10786550,
title = {What Affects Patient (Dis)satisfaction? Analyzing Online Doctor Ratings with a Joint Topic-Sentiment Model},
author = {{Michael J. Paul} and {Byron C. Wallace} and {Mark Dredze}},
year = 2013,
month = {6},
booktitle = {AAAI Conference on Artificial Intelligence},
url = {https://www.semanticscholar.org/paper/a23628e9d88cacafc35454ba77047f3de2e69f86},
}

Tomas Figliolia and A. Andreou, “Representation of temporal coherence: CHAINS algorithm and FPGA implementation,” in Annual Conference on Information Sciences and Systems, 2013.
[BibTeX] [Link]

@inproceedings{24095543,
title = {Representation of temporal coherence: CHAINS algorithm and FPGA implementation},
author = {{Tomas Figliolia} and {A. Andreou}},
year = 2013,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/083ad5dd283be19f45b1988c7e95f178016d7903},
}

Thomas S. Murray, P. Pouliquen, and A. Andreou, “8-channel 20 kHz to 200 MHz Nyquist and compressive sampler in 0.5 μm CMOS,” in Electronics Letters, 2013.
[BibTeX] [Link]

@inproceedings{56578217,
title = {8-channel 20 kHz to 200 MHz Nyquist and compressive sampler in 0.5 μm CMOS},
author = {{Thomas S. Murray} and {P. Pouliquen} and {A. Andreou}},
year = 2013,
month = {1},
booktitle = {Electronics Letters},
url = {https://www.semanticscholar.org/paper/261ac06da691014ee1c0206956fda2a749f2248f},
}

Tomas Figliolia, Daniel R. Mendat, A. Russell, Thomas S. Murray, Ernst Nieburyk, R. Etienne-Cummings, and A. Andreou, “Auditory modulation of visual proto-object formation in a hierarchical auditory-visual saliency map,” in Annual Conference on Information Sciences and Systems, 2013.
[BibTeX] [Link]

@inproceedings{20162731,
title = {Auditory modulation of visual proto-object formation in a hierarchical auditory-visual saliency map},
author = {{Tomas Figliolia} and {Daniel R. Mendat} and {A. Russell} and {Thomas S. Murray} and {Ernst Nieburyk} and {R. Etienne-Cummings} and {A. Andreou}},
year = 2013,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/72d30db866851bf56321690cafa2a98d12b3cf40},
}

Thomas S. Murray, P. Pouliquen, and A. Andreou, “Design of configurable chipping sequence generator for high-speed parallel samplers,” in Electronics Letters, 2013.
[BibTeX] [Link]

@inproceedings{62711320,
title = {Design of configurable chipping sequence generator for high-speed parallel samplers},
author = {{Thomas S. Murray} and {P. Pouliquen} and {A. Andreou}},
year = 2013,
month = {7},
booktitle = {Electronics Letters},
url = {https://www.semanticscholar.org/paper/eeda41683e5fc2b3d051e734272ab7577b6d3488},
}

S. Dura-Bernal, Guillaume Garreau, J. Georgiou, A. Andreou, S. Denham, and T. Wennekers, “Multimodal Integration of Micro-Doppler Sonar and auditory signals for Behavior Classification with convolutional Networks,” in International Journal of Neural Systems, 2013.
[BibTeX] [Link]

@inproceedings{91844,
title = {Multimodal Integration of Micro-Doppler Sonar and auditory signals for Behavior Classification with convolutional Networks},
author = {{S. Dura-Bernal} and {Guillaume Garreau} and {J. Georgiou} and {A. Andreou} and {S. Denham} and {T. Wennekers}},
year = 2013,
month = {8},
booktitle = {International Journal of Neural Systems},
url = {https://www.semanticscholar.org/paper/98259ddcfb6e054d516de404f8b0de5d442f1420},
}

Guillaume Garreau, Eleni Proxenou, A. Andreou, and J. Georgiou, “Person localization through ground vibrations using a sand-scorpion inspired spiking neural network,” in Annual Conference on Information Sciences and Systems, 2013.
[BibTeX] [Link]

@inproceedings{2683521,
title = {Person localization through ground vibrations using a sand-scorpion inspired spiking neural network},
author = {{Guillaume Garreau} and {Eleni Proxenou} and {A. Andreou} and {J. Georgiou}},
year = 2013,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/99669fcc500dfaf71212ca746692094fc44c174e},
}

D. Rao, Paul McNamee, and Mark Dredze, “Entity Linking: Finding Extracted Entities in a Knowledge Base,” in Multi-source, Multilingual Information Extraction and Summarization, 2013.
[BibTeX] [Link]

@inproceedings{6420241,
title = {Entity Linking: Finding Extracted Entities in a Knowledge Base},
author = {{D. Rao} and {Paul McNamee} and {Mark Dredze}},
year = 2013,
booktitle = {Multi-source, Multilingual Information Extraction and Summarization},
url = {https://www.semanticscholar.org/paper/35d4af572e687228a8dd2241f85d7a833fcf5e5d},
}

Joseph H. Lin, P. Pouliquen, and A. Andreou, “All digital programmable Gaussian pulse generator for ultra-wideband transmitter,” in Annual Conference on Information Sciences and Systems, 2013.
[BibTeX] [Link]

@inproceedings{14694094,
title = {All digital programmable Gaussian pulse generator for ultra-wideband transmitter},
author = {{Joseph H. Lin} and {P. Pouliquen} and {A. Andreou}},
year = 2013,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/afd123b749f1a22016501bb9efbd7b8f86316be7},
}

Carolina Parada, Mark Dredze, A. Sethy, and A. Rastrow, “Sub-Lexical and Contextual Modeling of Out-of-Vocabulary Words in Speech Recognition.” 2013.
[BibTeX] [Link]

@inproceedings{9011125,
title = {Sub-Lexical and Contextual Modeling of Out-of-Vocabulary Words in Speech Recognition},
author = {{Carolina Parada} and {Mark Dredze} and {A. Sethy} and {A. Rastrow}},
year = 2013,
booktitle = {},
url = {https://www.semanticscholar.org/paper/06988c9227cd8328ce54fc243c77797d40976020},
}

A. Andreou, Thomas S. Murray, and P. Pouliquen, “Signal to symbol converters: Overview, opportunities and challenges,” in Annual Conference on Information Sciences and Systems, 2013.
[BibTeX] [Link]

@inproceedings{16372867,
title = {Signal to symbol converters: Overview, opportunities and challenges},
author = {{A. Andreou} and {Thomas S. Murray} and {P. Pouliquen}},
year = 2013,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/7a142dddd7c15a3915f8079822c11cdabb3c1dcd},
}

Damianos G. Karakos, Mark Dredze, and S. Khudanpur, “Estimating Confusions in the ASR Channel for Improved Topic-based Language Model Adaptation,” in arXiv.org, 2013.
[BibTeX] [Link]

@inproceedings{15808834,
title = {Estimating Confusions in the ASR Channel for Improved Topic-based Language Model Adaptation},
author = {{Damianos G. Karakos} and {Mark Dredze} and {S. Khudanpur}},
year = 2013,
month = {3},
booktitle = {arXiv.org},
url = {https://www.semanticscholar.org/paper/860a3390dd415290981591a5158ac6dc602d8a5f},
}

Mona T. Diab, Mark Dredze, S. Harabagiu, and Dragomir R. Radev, “Overview of the special session on semantics and sociolinguistics in social media.” 2012.
[BibTeX] [Link]

@inproceedings{64230074,
title = {Overview of the special session on semantics and sociolinguistics in social media},
author = {{Mona T. Diab} and {Mark Dredze} and {S. Harabagiu} and {Dragomir R. Radev}},
year = 2012,
month = {12},
booktitle = {},
url = {https://www.semanticscholar.org/paper/4a9d1cb69246bd3530d1eef08eaf666aa6ee1fdb},
}

Michael J. Paul and Mark Dredze, “Factorial LDA: Sparse Multi-Dimensional Text Models,” in Neural Information Processing Systems, 2012.
[BibTeX] [Link]

@inproceedings{1860841,
title = {Factorial LDA: Sparse Multi-Dimensional Text Models},
author = {{Michael J. Paul} and {Mark Dredze}},
year = 2012,
month = {12},
booktitle = {Neural Information Processing Systems},
url = {https://www.semanticscholar.org/paper/8fefa7f27808f578ee6b01443dce8a658201f0c8},
}

J. Jiang, A. Teichert, H. {Daumé III}, and J. Eisner, “Learned Prioritization for Trading Off Accuracy and Speed,” in Advances in Neural Information Processing Systems 25 (NeurIPS), Lake Tahoe, NV, 2012, p. 1331–1339.
[BibTeX] [Link]

@InProceedings{jiang-et-al-2012-nips,
author = "Jiarong Jiang and Adam Teichert and Hal {Daum\'{e}
III} and Jason Eisner",
title = "Learned Prioritization for Trading Off Accuracy and
Speed",
booktitle = "Advances in Neural Information Processing Systems 25
(NeurIPS)",
pages = "1331--1339",
year = "2012",
month = dec,
address = "Lake Tahoe, NV",
URL = "http://cs.jhu.edu/~jason/papers/#jiang-et-al-2012-nips",
}

H. He, H. Daumé III, and J. Eisner, “Imitation Learning by Coaching,” in Advances in Neural Information Processing Systems 25 (NeurIPS), Lake Tahoe, NV, 2012, p. 3149–3157.
[BibTeX] [Link]

@InProceedings{he-daume-eisner-2012-nips,
author = "He He and Hal {Daum\'{e} III} and Jason Eisner",
title = "Imitation Learning by Coaching",
booktitle = "Advances in Neural Information Processing Systems 25
(NeurIPS)",
pages = "3149--3157",
year = "2012",
month = dec,
address = "Lake Tahoe, NV",
URL = "http://cs.jhu.edu/~jason/papers/#he-daume-eisner-2012-nips",
}

V. Stoyanov and J. Eisner, “Easy-first Coreference Resolution,” in Proceedings of the 24th International Conference on Computational Linguistics (COLING), Mumbai, 2012, p. 2519–2534.
[BibTeX] [Link]

@InProceedings{stoyanov-eisner-2012-coling,
aclid = "C12-1154",
author = "Veselin Stoyanov and Jason Eisner",
title = "Easy-first Coreference Resolution",
booktitle = "Proceedings of the 24th International Conference on
Computational Linguistics (COLING)",
pages = "2519--2534",
year = "2012",
month = dec,
address = "Mumbai",
URL = "http://cs.jhu.edu/~jason/papers/#stoyanov-eisner-2012-coling",
}

Mark Dredze, “Models for Mining Public Health Information from Social Media.” 2012.
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@inproceedings{157114152,
title = {Models for Mining Public Health Information from Social Media},
author = {{Mark Dredze}},
year = 2012,
month = {11},
booktitle = {},
url = {https://www.semanticscholar.org/paper/9a0f64733f6f68217932c5e4c9742fe3a02f1728},
}

Michael J. Paul and Mark Dredze, “Experimenting with Drugs (and Topic Models): Multi-Dimensional Exploration of Recreational Drug Discussions,” in AAAI Fall Symposium: Information Retrieval and Knowledge Discovery in Biomedical Text, 2012.
[BibTeX] [Link]

@inproceedings{3048394,
title = {Experimenting with Drugs (and Topic Models): Multi-Dimensional Exploration of Recreational Drug Discussions},
author = {{Michael J. Paul} and {Mark Dredze}},
year = 2012,
month = {10},
booktitle = {AAAI Fall Symposium: Information Retrieval and Knowledge Discovery in Biomedical Text},
url = {https://www.semanticscholar.org/paper/8d7a70d094901d2bd700ab23fa6d2e9b066bde46},
}

H. Korth, K. Strohbehn, Francisco Tejada, A. Andreou, J. Kitching, and S. Knappe, “Miniature Absolute Scalar Magnetometer Based on the Rubidium Isotope 87Rb.” 2012.
[BibTeX] [Link]

@inproceedings{222602753,
title = {Miniature Absolute Scalar Magnetometer Based on the Rubidium Isotope 87Rb},
author = {{H. Korth} and {K. Strohbehn} and {Francisco Tejada} and {A. Andreou} and {J. Kitching} and {S. Knappe}},
year = 2012,
month = {10},
booktitle = {},
url = {https://www.semanticscholar.org/paper/31417310e9bd7abd7ee5275ca73cc2bf4b7b7495},
}

Alex Lamb, Michael J. Paul, and Mark Dredze, “Investigating Twitter as a Source for Studying Behavioral Responses to Epidemics,” in AAAI Fall Symposium: Information Retrieval and Knowledge Discovery in Biomedical Text, 2012.
[BibTeX] [Link]

@inproceedings{1573045,
title = {Investigating Twitter as a Source for Studying Behavioral Responses to Epidemics},
author = {{Alex Lamb} and {Michael J. Paul} and {Mark Dredze}},
year = 2012,
month = {10},
booktitle = {AAAI Fall Symposium: Information Retrieval and Knowledge Discovery in Biomedical Text},
url = {https://www.semanticscholar.org/paper/0aa787fb15a9a5aef417eed43b07418410f2cfaa},
}

Atul Nakhasi, R. Passarella, Sarah G. Bell, Michael J. Paul, Mark Dredze, and P. Pronovost, “Malpractice and Malcontent: Analyzing Medical Complaints in Twitter,” in AAAI Fall Symposium: Information Retrieval and Knowledge Discovery in Biomedical Text, 2012.
[BibTeX] [Link]

@inproceedings{31827846,
title = {Malpractice and Malcontent: Analyzing Medical Complaints in Twitter},
author = {{Atul Nakhasi} and {R. Passarella} and {Sarah G. Bell} and {Michael J. Paul} and {Mark Dredze} and {P. Pronovost}},
year = 2012,
month = {10},
booktitle = {AAAI Fall Symposium: Information Retrieval and Knowledge Discovery in Biomedical Text},
url = {https://www.semanticscholar.org/paper/fd7064b1f28ada678659656311879ab7c377d04c},
}

N. W. Filardo and J. Eisner, “A Flexible Solver for Finite Arithmetic Circuits,” in Technical Communications of the 28th International Conference on Logic Programming (ICLP), Budapest, 2012, p. 425–438.
[BibTeX] [Link]

@InProceedings{filardo-eisner-2012-iclp,
author = "Nathaniel Wesley Filardo and Jason Eisner",
title = "A Flexible Solver for Finite Arithmetic Circuits",
booktitle = "Technical Communications of the 28th International
Conference on Logic Programming (ICLP)",
editor = "Agostino Dovier and V\'{\i}tor Santos Costa",
series = "Leibniz International Proceedings in Informatics
(LIPIcs)",
volume = "17",
pages = "425--438",
ISBN = "978-3-939897-43-9",
year = "2012",
month = sep,
address = "Budapest",
URL = "http://cs.jhu.edu/~jason/papers/#filardo-eisner-2012-iclp",
}

A. Rastrow, M. Dredze, and S. Khudanpur, “Fast Syntactic Analysis for Statistical Language Modeling via Substructure Sharing and Uptraining,” in Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Jeju Island, Korea, 2012, p. 175–183.
[BibTeX] [Link]

@inproceedings{rastrow-etal-2012-fast,
title = "Fast Syntactic Analysis for Statistical Language Modeling via Substructure Sharing and Uptraining",
author = "Rastrow, Ariya and
Dredze, Mark and
Khudanpur, Sanjeev",
editor = "Li, Haizhou and
Lin, Chin-Yew and
Osborne, Miles and
Lee, Gary Geunbae and
Park, Jong C.",
booktitle = "Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = jul,
year = "2012",
address = "Jeju Island, Korea",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P12-1019",
pages = "175--183",
}

N. Andrews, J. Eisner, and M. Dredze, “Name Phylogeny: A Generative Model of String Variation,” in Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, Jeju Island, Korea, 2012, p. 344–355.
[BibTeX] [Link]

@inproceedings{andrews-etal-2012-name,
title = "Name Phylogeny: A Generative Model of String Variation",
author = "Andrews, Nicholas and
Eisner, Jason and
Dredze, Mark",
editor = "Tsujii, Jun{'}ichi and
Henderson, James and
Pa{\c{s}}ca, Marius",
booktitle = "Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning",
month = jul,
year = "2012",
address = "Jeju Island, Korea",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D12-1032",
pages = "344--355",
}

M. Joshi, M. Dredze, W. W. Cohen, and C. Rosé, “Multi-Domain Learning: When Do Domains Matter?,” in Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, Jeju Island, Korea, 2012, p. 1302–1312.
[BibTeX] [Link]

@inproceedings{joshi-etal-2012-multi,
title = "Multi-Domain Learning: When Do Domains Matter?",
author = "Joshi, Mahesh and
Dredze, Mark and
Cohen, William W. and
Ros{\'e}, Carolyn",
editor = "Tsujii, Jun{'}ichi and
Henderson, James and
Pa{\c{s}}ca, Marius",
booktitle = "Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning",
month = jul,
year = "2012",
address = "Jeju Island, Korea",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D12-1119",
pages = "1302--1312",
}

N. Andrews, J. Eisner, and M. Dredze, “Name Phylogeny: A Generative Model of String Variation,” in Proceedings of the Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL), Jeju, Korea, 2012, p. 344–355.
[BibTeX] [Link]

@InProceedings{andrews-eisner-dredze-2012,
aclid = "D12-1032",
author = "Nicholas Andrews and Jason Eisner and Mark Dredze",
title = "Name Phylogeny: {A} Generative Model of String
Variation",
booktitle = "Proceedings of the Conference on Empirical Methods in
Natural Language Processing and Computational Natural
Language Learning (EMNLP-CoNLL)",
pages = "344--355",
year = "2012",
month = jul,
address = "Jeju, Korea",
URL = "http://cs.jhu.edu/~jason/papers/#andrews-eisner-dredze-2012",
}

M. R. Gormley, M. Dredze, B. Van Durme, and J. Eisner, “Shared Components Topic Models,” in Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Montréal, Canada, 2012, p. 783–792.
[BibTeX] [Link]

@inproceedings{gormley-etal-2012-shared,
title = "Shared Components Topic Models",
author = "Gormley, Matthew R. and
Dredze, Mark and
Van Durme, Benjamin and
Eisner, Jason",
editor = "Fosler-Lussier, Eric and
Riloff, Ellen and
Bangalore, Srinivas",
booktitle = "Proceedings of the 2012 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies",
month = jun,
year = "2012",
address = "Montr{\'e}al, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N12-1096",
pages = "783--792",
}

S. Green, N. Andrews, M. R. Gormley, M. Dredze, and C. D. Manning, “Entity Clustering Across Languages,” in Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Montréal, Canada, 2012, p. 60–69.
[BibTeX] [Link]

@inproceedings{green-etal-2012-entity,
title = "Entity Clustering Across Languages",
author = "Green, Spence and
Andrews, Nicholas and
Gormley, Matthew R. and
Dredze, Mark and
Manning, Christopher D.",
editor = "Fosler-Lussier, Eric and
Riloff, Ellen and
Bangalore, Srinivas",
booktitle = "Proceedings of the 2012 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies",
month = jun,
year = "2012",
address = "Montr{\'e}al, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N12-1007",
pages = "60--69",
}

A. Rastrow, S. Khudanpur, and M. Dredze, “Revisiting the Case for Explicit Syntactic Information in Language Models,” in Proceedings of the NAACL-HLT 2012 Workshop: Will We Ever Really Replace the N-gram Model? On the Future of Language Modeling for HLT, Montréal, Canada, 2012, p. 50–58.
[BibTeX] [Link]

@inproceedings{rastrow-etal-2012-revisiting,
title = "Revisiting the Case for Explicit Syntactic Information in Language Models",
author = "Rastrow, Ariya and
Khudanpur, Sanjeev and
Dredze, Mark",
editor = "Ramabhadran, Bhuvana and
Khudanpur, Sanjeev and
Arisoy, Ebru",
booktitle = "Proceedings of the {NAACL}-{HLT} 2012 Workshop: Will We Ever Really Replace the N-gram Model? On the Future of Language Modeling for {HLT}",
month = jun,
year = "2012",
address = "Montr{\'e}al, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W12-2707",
pages = "50--58",
}

J. Jiang, A. Teichert, H. {Daumé III}, and J. Eisner, “Learned Prioritization for Trading Off Accuracy and Speed,” in ICML Workshop on Inferning: Interactions between Inference and Learning, Edinburgh, 2012.
[BibTeX] [Link]

@InProceedings{jiang-et-al-2012-icmlw,
author = "Jiarong Jiang and Adam Teichert and Hal {Daum\'{e}
III} and Jason Eisner",
title = "Learned Prioritization for Trading Off Accuracy and
Speed",
booktitle = "ICML Workshop on Inferning: Interactions between
Inference and Learning",
note = "7 pages",
year = "2012",
month = jun,
address = "Edinburgh",
URL = "http://cs.jhu.edu/~jason/papers/#jiang-et-al-2012-icmlw",
}

H. He, H. Daumé III, and J. Eisner, “Cost-Sensitive Dynamic Feature Selection,” in ICML Workshop on Inferning: Interactions between Inference and Learning, Edinburgh, 2012.
[BibTeX] [Link]

@InProceedings{he-daume-eisner-2012-icmlw,
author = "He He and Hal {Daum\'{e} III} and Jason Eisner",
title = "Cost-Sensitive Dynamic Feature Selection",
booktitle = "ICML Workshop on Inferning: Interactions between
Inference and Learning",
note = "6 pages",
year = "2012",
month = jun,
address = "Edinburgh",
URL = "http://cs.jhu.edu/~jason/papers/#he-daume-eisner-2012-icmlw",
}

V. Stoyanov and J. Eisner, “Fast and Accurate Prediction via Evidence-Specific MRF Structure,” in ICML Workshop on Inferning: Interactions between Inference and Learning, Edinburgh, 2012.
[BibTeX] [Link]

@InProceedings{stoyanov-eisner-2012-icmlw,
author = "Veselin Stoyanov and Jason Eisner",
title = "Fast and Accurate Prediction via Evidence-Specific
{MRF} Structure",
booktitle = "ICML Workshop on Inferning: Interactions between
Inference and Learning",
note = "6 pages",
year = "2012",
month = jun,
address = "Edinburgh",
URL = "http://cs.jhu.edu/~jason/papers/#stoyanov-eisner-2012-icmlw",
}

M. R. Gormley, M. Dredze, B. {Van Durme}, and J. Eisner, “Shared Components Topic Models,” in Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT), Montreal, 2012, p. 783–792.
[BibTeX] [Link]

@InProceedings{gormley-et-al-2012,
aclid = "N12-1096",
author = "Matthew R. Gormley and Mark Dredze and Benjamin {Van
Durme} and Jason Eisner",
title = "Shared Components Topic Models",
booktitle = "Proceedings of the 2012 Conference of the North
American Chapter of the Association for Computational
Linguistics: Human Language Technologies (NAACL-HLT)",
pages = "783--792",
year = "2012",
month = jun,
address = "Montreal",
URL = "http://cs.jhu.edu/~jason/papers/#gormley-et-al-2012",
}

M. Paul and J. Eisner, “Implicitly Intersecting Weighted Automata using Dual Decomposition,” in Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT), Montreal, 2012, p. 232–242.
[BibTeX] [Link]

@InProceedings{paul-eisner-2012,
aclid = "N12-1024",
author = "Michael Paul and Jason Eisner",
title = "Implicitly Intersecting Weighted Automata using Dual
Decomposition",
booktitle = "Proceedings of the 2012 Conference of the North
American Chapter of the Association for Computational
Linguistics: Human Language Technologies (NAACL-HLT)",
pages = "232--242",
year = "2012",
month = jun,
address = "Montreal",
URL = "http://cs.jhu.edu/~jason/papers/#paul-eisner-2012",
}

J. Smith and J. Eisner, “Unsupervised Learning on an Approximate Corpus,” in Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT), Montreal, 2012, p. 131–141.
[BibTeX] [Link]

@InProceedings{smith-eisner-2012,
aclid = "N12-1014",
author = "Jason Smith and Jason Eisner",
title = "Unsupervised Learning on an Approximate Corpus",
booktitle = "Proceedings of the 2012 Conference of the North
American Chapter of the Association for Computational
Linguistics: Human Language Technologies (NAACL-HLT)",
pages = "131--141",
year = "2012",
month = jun,
address = "Montreal",
URL = "http://cs.jhu.edu/~jason/papers/#smith-eisner-2012",
}

V. Stoyanov and J. Eisner, “Minimum-Risk Training of Approximate CRF-Based NLP Systems,” in Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT), Montreal, 2012, p. 120–130.
[BibTeX] [Link]

@InProceedings{stoyanov-eisner-2012-naacl,
aclid = "N12-1013",
author = "Veselin Stoyanov and Jason Eisner",
title = "Minimum-Risk Training of Approximate {CRF}-Based {NLP}
Systems",
booktitle = "Proceedings of the 2012 Conference of the North
American Chapter of the Association for Computational
Linguistics: Human Language Technologies (NAACL-HLT)",
pages = "120--130",
year = "2012",
month = jun,
address = "Montreal",
URL = "http://cs.jhu.edu/~jason/papers/#stoyanov-eisner-2012-naacl",
}

K. Crammer, Alex Kulesza, and Mark Dredze, “New ℌ∞ bounds for the recursive least squares algorithm exploiting input structure,” in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2012.
[BibTeX] [Link]

@inproceedings{11344374,
title = {New ℌ∞ bounds for the recursive least squares algorithm exploiting input structure},
author = {{K. Crammer} and {Alex Kulesza} and {Mark Dredze}},
year = 2012,
month = {3},
booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
url = {https://www.semanticscholar.org/paper/1f0b3a31cd3475ed8b83e23917b0b100d3c51a9e},
}

T. Stouraitis, Zhi-Pei Liang, Gary G. Yen, Gert Cauwenberghs, R. Etienne-Cummings, A. Andreou, Amine Bermak, Alison Burdett, Sandro Carrara, Krishnendu Chakrabarty, S. Chakrabartty, Jie Chen, T. Delbruck, Timothy J. Denison, S. DeWeerth, Emmanuel M. Drakakis, Roman Genov, Julius Georgiou, Edmund Y. L Am, Steffen Leonhardt, Yong Lian, Shih-Chii Liu, Wentai Liu, A. J. Mason, Tamás Roska, Rahul Sarpeshkar, M. Sawan, Kenneth L. Shepard, Bertram E. Shi, M. Stanaćević, and J. V. D. Spiegel, “IEEE Transactions on Biomedical Circuits and Systems,” in IEEE Transactions on Biomedical Circuits and Systems, 2012.
[BibTeX] [Link]

@inproceedings{263807607,
title = {IEEE Transactions on Biomedical Circuits and Systems},
author = {{T. Stouraitis} and {Zhi-Pei Liang} and {Gary G. Yen} and {Gert Cauwenberghs} and {R. Etienne-Cummings} and {A. Andreou} and {Amine Bermak} and {Alison Burdett} and {Sandro Carrara} and {Krishnendu Chakrabarty} and {S. Chakrabartty} and {Jie Chen} and {T. Delbruck} and {Timothy J. Denison} and {S. DeWeerth} and {Emmanuel M. Drakakis} and {Roman Genov} and {Julius Georgiou} and {Edmund Y. L Am} and {Steffen Leonhardt} and {Yong Lian} and {Shih-Chii Liu} and {Wentai Liu} and {A. J. Mason} and {Tamás Roska} and {Rahul Sarpeshkar} and {M. Sawan} and {Kenneth L. Shepard} and {Bertram E. Shi} and {M. Stanaćević} and {J. V. D. Spiegel}},
year = 2012,
booktitle = {IEEE Transactions on Biomedical Circuits and Systems},
url = {https://www.semanticscholar.org/paper/5224c9da3353cdec21724c67ebdc22fb63c9cc9c},
}

H. Rostro-González, Guillaume Garreau, A. Andreou, J. Georgiou, J. H. Barrón-Zambrano, and C. Torres-Huitzil, “An FPGA-based approach for parameter estimation in spiking neural networks,” in 2012 IEEE International Symposium on Circuits and Systems, 2012.
[BibTeX] [Link]

@inproceedings{40918504,
title = {An FPGA-based approach for parameter estimation in spiking neural networks},
author = {{H. Rostro-González} and {Guillaume Garreau} and {A. Andreou} and {J. Georgiou} and {J. H. Barrón-Zambrano} and {C. Torres-Huitzil}},
year = 2012,
month = {5},
booktitle = {2012 IEEE International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/77e14a1f04ef133cebb10ab9e8162ac4204cbe8e},
}

A. Rastrow, Mark Dredze, and S. Khudanpur, “Efficient Structured Language Modeling for Speech Recognition,” in Interspeech, 2012.
[BibTeX] [Link]

@inproceedings{12189517,
title = {Efficient Structured Language Modeling for Speech Recognition},
author = {{A. Rastrow} and {Mark Dredze} and {S. Khudanpur}},
year = 2012,
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/f989e2daf81937b4111f5ad79f785c5d996a8098},
}

Damianos G. Karakos, Brian Roark, Izhak Shafran, Kenji Sagae, M. Lehr, Emily Tucker Prud’hommeaux, Puyang Xu, N. Glenn, S. Khudanpur, M. Saraçlar, D. Bikel, Mark Dredze, Chris Callison-Burch, Yuan Cao, Keith B. Hall, E. Hasler, Philipp Koehn, Adam Lopez, Matt Post, and Darcey Riley, “Deriving conversation-based features from unlabeled speech for discriminative language modeling,” in Interspeech, 2012.
[BibTeX] [Link]

@inproceedings{6190744,
title = {Deriving conversation-based features from unlabeled speech for discriminative language modeling},
author = {{Damianos G. Karakos} and {Brian Roark} and {Izhak Shafran} and {Kenji Sagae} and {M. Lehr} and {Emily Tucker Prud'hommeaux} and {Puyang Xu} and {N. Glenn} and {S. Khudanpur} and {M. Saraçlar} and {D. Bikel} and {Mark Dredze} and {Chris Callison-Burch} and {Yuan Cao} and {Keith B. Hall} and {E. Hasler} and {Philipp Koehn} and {Adam Lopez} and {Matt Post} and {Darcey Riley}},
year = 2012,
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/3873e60de2d20aa33829e2d3d79221e716785546},
}

Nicholas Andrews, Jason Eisner, and Mark Dredze, “A Generative Model of String Variation.” 2012.
[BibTeX] [Link]

@inproceedings{61990873,
title = {A Generative Model of String Variation},
author = {{Nicholas Andrews} and {Jason Eisner} and {Mark Dredze}},
year = 2012,
booktitle = {},
url = {https://www.semanticscholar.org/paper/be5b25c42bc584a4d66dae90680a370ca50d6b1c},
}

Lana Yeganova, R. Dogan, Vahan Grigoryan, and Mark Dredze, “Information retrieval and knowledge discovery in biomedical text : papers from the AAAI Fall Symposium.” 2012.
[BibTeX] [Link]

@inproceedings{60099367,
title = {Information retrieval and knowledge discovery in biomedical text : papers from the AAAI Fall Symposium},
author = {{Lana Yeganova} and {R. Dogan} and {Vahan Grigoryan} and {Mark Dredze}},
year = 2012,
booktitle = {},
url = {https://www.semanticscholar.org/paper/9c92b90a1bfba1edb4ce8a52f421bbc14abb98c8},
}

Mark Dredze, “How Social Media Will Change Public Health,” in IEEE Intelligent Systems, 2012.
[BibTeX] [Link]

@inproceedings{9541287,
title = {How Social Media Will Change Public Health},
author = {{Mark Dredze}},
year = 2012,
month = {7},
booktitle = {IEEE Intelligent Systems},
url = {https://www.semanticscholar.org/paper/537c1f378830e056e9d7f6e919d16dd007398070},
}

Charbel G. Rizk, Joseph H. Lin, S. Kennerly, P. Pouliquen, A. Goldberg, and A. Andreou, “High-performance, event-driven, low-cost, and SWaP imaging sensor for hostile fire detection, homeland protection, and border security,” in Defense + Commercial Sensing, 2012.
[BibTeX] [Link]

@inproceedings{120457468,
title = {High-performance, event-driven, low-cost, and SWaP imaging sensor for hostile fire detection, homeland protection, and border security},
author = {{Charbel G. Rizk} and {Joseph H. Lin} and {S. Kennerly} and {P. Pouliquen} and {A. Goldberg} and {A. Andreou}},
year = 2012,
month = {5},
booktitle = {Defense + Commercial Sensing},
url = {https://www.semanticscholar.org/paper/ae9247800f9a9c65692d4cc70a421332752d122d},
}

K. Crammer, Mark Dredze, and Fernando C Pereira, “Confidence-Weighted Linear Classification for Text Categorization,” in Journal of machine learning research, 2012.
[BibTeX] [Link]

@inproceedings{12975143,
title = {Confidence-Weighted Linear Classification for Text Categorization},
author = {{K. Crammer} and {Mark Dredze} and {Fernando C Pereira}},
year = 2012,
month = {3},
booktitle = {Journal of machine learning research},
url = {https://www.semanticscholar.org/paper/e33f036549c0aed1dc3a4485effa8a0a5b4428c6},
}

Thomas J. Dawidczyk, G. Johns, R. Ozgun, Olivia Alley, A. Andreou, N. Marković, and H. Katz, “Kelvin probe microscopic visualization of charge storage at polystyrene interfaces with pentacene and gold,” in Applied Physics Letters, 2012.
[BibTeX] [Link]

@inproceedings{120899976,
title = {Kelvin probe microscopic visualization of charge storage at polystyrene interfaces with pentacene and gold},
author = {{Thomas J. Dawidczyk} and {G. Johns} and {R. Ozgun} and {Olivia Alley} and {A. Andreou} and {N. Marković} and {H. Katz}},
year = 2012,
month = {2},
booktitle = {Applied Physics Letters},
url = {https://www.semanticscholar.org/paper/04beaeebae569503099bb62aa0a40d7fb4142539},
}

Hoyoul Kong, Thomas J. Dawidczyk, R. Ozgun, A. Andreou, and H. Katz, “Printed Organic Electronic Sensors.” 2012.
[BibTeX] [Link]

@inproceedings{97153351,
title = {Printed Organic Electronic Sensors},
author = {{Hoyoul Kong} and {Thomas J. Dawidczyk} and {R. Ozgun} and {A. Andreou} and {H. Katz}},
year = 2012,
booktitle = {},
url = {https://www.semanticscholar.org/paper/d7fa8dd424a8bf5338765ebc6dc2696c1b37e86d},
}

Joseph H. Lin, P. Pouliquen, A. Andreou, A. Goldberg, and Charbel G. Rizk, “Flexible readout and integration sensor (FRIS): a bio-inspired, system-on-chip, event-based readout architecture,” in Defense + Commercial Sensing, 2012.
[BibTeX] [Link]

@inproceedings{110257846,
title = {Flexible readout and integration sensor (FRIS): a bio-inspired, system-on-chip, event-based readout architecture},
author = {{Joseph H. Lin} and {P. Pouliquen} and {A. Andreou} and {A. Goldberg} and {Charbel G. Rizk}},
year = 2012,
month = {5},
booktitle = {Defense + Commercial Sensing},
url = {https://www.semanticscholar.org/paper/2b7257e3fb6ac6cd91972beb4ba8826008192ecf},
}

R. Passarella, Atul Nakhasi, Sarah G. Bell, Michael J. Paul, P. Pronovost, and Mark Dredze, “Twitter as a Source for Learning about Patient Safety Events,” in American Medical Informatics Association Annual Symposium, 2012.
[BibTeX] [Link]

@inproceedings{46321860,
title = {Twitter as a Source for Learning about Patient Safety Events},
author = {{R. Passarella} and {Atul Nakhasi} and {Sarah G. Bell} and {Michael J. Paul} and {P. Pronovost} and {Mark Dredze}},
year = 2012,
booktitle = {American Medical Informatics Association Annual Symposium},
url = {https://www.semanticscholar.org/paper/d663e0a7f5475d8c4902a2fd31f14725cf2a2ef7},
}

A. Cassidy and A. Andreou, “Beyond Amdahl’s Law: An Objective Function That Links Multiprocessor Performance Gains to Delay and Energy,” in IEEE transactions on computers, 2012.
[BibTeX] [Link]

@inproceedings{8714713,
title = {Beyond Amdahl's Law: An Objective Function That Links Multiprocessor Performance Gains to Delay and Energy},
author = {{A. Cassidy} and {A. Andreou}},
year = 2012,
month = {8},
booktitle = {IEEE transactions on computers},
url = {https://www.semanticscholar.org/paper/c4466acbd9ba0a2d2e139ef5a793b613aaf02b1e},
}

Damianos G. Karakos, Brian Roark, Izhak Shafran, Kenji Sagae, M. Lehr, Emily Tucker Prud’hommeaux, Puyang Xu, N. Glenn, S. Khudanpur, M. Saraçlar, D. Bikel, Mark Dredze, Chris Callison-Burch, Yuan Cao, Keith B. Hall, E. Hasler, Philipp Koehn, Adam Lopez, Matt Post, and Darcey Riley, “INTERSPEECH 2012, 13th Annual Conference of the International Speech Communication Association, Portland, Oregon, USA, September 9-13, 2012.” 2012.
[BibTeX] [Link]

@inproceedings{186771008,
title = {INTERSPEECH 2012, 13th Annual Conference of the International Speech Communication Association, Portland, Oregon, USA, September 9-13, 2012},
author = {{Damianos G. Karakos} and {Brian Roark} and {Izhak Shafran} and {Kenji Sagae} and {M. Lehr} and {Emily Tucker Prud'hommeaux} and {Puyang Xu} and {N. Glenn} and {S. Khudanpur} and {M. Saraçlar} and {D. Bikel} and {Mark Dredze} and {Chris Callison-Burch} and {Yuan Cao} and {Keith B. Hall} and {E. Hasler} and {Philipp Koehn} and {Adam Lopez} and {Matt Post} and {Darcey Riley}},
year = 2012,
booktitle = {},
url = {https://www.semanticscholar.org/paper/af034b0e893a0a24e41cdb54afb35d4250407f50},
}

T. Serrano-Gotarredona, B. Linares-Barranco, and A. Andreou, “Adaptive Resonance Theory Microchips: Circuit Design Techniques.” 2012.
[BibTeX] [Link]

@inproceedings{59705579,
title = {Adaptive Resonance Theory Microchips: Circuit Design Techniques},
author = {{T. Serrano-Gotarredona} and {B. Linares-Barranco} and {A. Andreou}},
year = 2012,
month = {9},
booktitle = {},
url = {https://www.semanticscholar.org/paper/693494c7fb5f461e5c980df505b9a78c9cc5c539},
}

A. Andreou, “Interview with Andreas G. Andreou,” in Electronics Letters, 2011.
[BibTeX] [Link]

@inproceedings{62620872,
title = {Interview with Andreas G. Andreou},
author = {{A. Andreou}},
year = 2011,
month = {12},
booktitle = {Electronics Letters},
url = {https://www.semanticscholar.org/paper/f313ea547da8588136cd316f99601b0f1ee7f7bf},
}

A. Rastrow, Mark Dredze, and S. Khudanpur, “Adapting n-gram maximum entropy language models with conditional entropy regularization,” in 2011 IEEE Workshop on Automatic Speech Recognition & Understanding, 2011.
[BibTeX] [Link]

@inproceedings{14363701,
title = {Adapting n-gram maximum entropy language models with conditional entropy regularization},
author = {{A. Rastrow} and {Mark Dredze} and {S. Khudanpur}},
year = 2011,
month = {12},
booktitle = {2011 IEEE Workshop on Automatic Speech Recognition & Understanding},
url = {https://www.semanticscholar.org/paper/46e3aa6c828f372e6d43f0b1fb00613f02bb0a8e},
}

Damianos G. Karakos, Mark Dredze, K. Church, A. Jansen, and S. Khudanpur, “Estimating document frequencies in a speech corpus,” in 2011 IEEE Workshop on Automatic Speech Recognition & Understanding, 2011.
[BibTeX] [Link]

@inproceedings{6914375,
title = {Estimating document frequencies in a speech corpus},
author = {{Damianos G. Karakos} and {Mark Dredze} and {K. Church} and {A. Jansen} and {S. Khudanpur}},
year = 2011,
month = {12},
booktitle = {2011 IEEE Workshop on Automatic Speech Recognition & Understanding},
url = {https://www.semanticscholar.org/paper/990c9260b6d2a33aeaba30e4640ec59d709864fc},
}

A. Andreou, “Johns Hopkins on the chip: microsystems and cognitive machines for sustainable, affordable, personalised medicine and healthcare,” in Electronics Letters, 2011.
[BibTeX] [Link]

@inproceedings{267820863,
title = {Johns Hopkins on the chip: microsystems and cognitive machines for sustainable, affordable, personalised medicine and healthcare},
author = {{A. Andreou}},
year = 2011,
month = {12},
booktitle = {Electronics Letters},
url = {https://www.semanticscholar.org/paper/51fac499815b58036986a1b026f813bbdf90d94f},
}

A. Rastrow, Mark Dredze, and S. Khudanpur, “Efficient discriminative training of long-span language models,” in 2011 IEEE Workshop on Automatic Speech Recognition & Understanding, 2011.
[BibTeX] [Link]

@inproceedings{9645306,
title = {Efficient discriminative training of long-span language models},
author = {{A. Rastrow} and {Mark Dredze} and {S. Khudanpur}},
year = 2011,
month = {12},
booktitle = {2011 IEEE Workshop on Automatic Speech Recognition & Understanding},
url = {https://www.semanticscholar.org/paper/8924c38cdd8fed464a9808524e45930a6164ca37},
}

Guillaume Garreau, C. M. Andreou, A. Andreou, J. Georgiou, S. Dura-Bernal, T. Wennekers, and S. Denham, “Gait-based person and gender recognition using micro-doppler signatures,” in Biomedical Circuits and Systems Conference, 2011.
[BibTeX] [Link]

@inproceedings{8578649,
title = {Gait-based person and gender recognition using micro-doppler signatures},
author = {{Guillaume Garreau} and {C. M. Andreou} and {A. Andreou} and {J. Georgiou} and {S. Dura-Bernal} and {T. Wennekers} and {S. Denham}},
year = 2011,
month = {12},
booktitle = {Biomedical Circuits and Systems Conference},
url = {https://www.semanticscholar.org/paper/10f61c695ecd47086397481753793b3dd0d264d7},
}

J. Eisner and H. Daumé III, “Learning Speed-Accuracy Tradeoffs in Nondeterministic Inference Algorithms,” in COST: NeurIPS Workshop on Computational Trade-offs in Statistical Learning, Sierra Nevada, Spain, 2011.
[BibTeX] [Link]

@InProceedings{eisner-daume-2011,
author = "Jason Eisner and Hal {Daum\'{e} III}",
title = "Learning Speed-Accuracy Tradeoffs in Nondeterministic
Inference Algorithms",
booktitle = "COST: NeurIPS Workshop on Computational Trade-offs in
Statistical Learning",
note = "5 pages",
year = "2011",
month = dec,
address = "Sierra Nevada, Spain",
URL = "http://cs.jhu.edu/~jason/papers/#eisner-daume-2011",
}

V. Stoyanov and J. Eisner, “Learning Cost-Aware, Loss-Aware Approximate Inference Policies for Probabilistic Graphical Models,” in COST: NeurIPS Workshop on Computational Trade-offs in Statistical Learning, Sierra Nevada, Spain, 2011.
[BibTeX] [Link]

@InProceedings{stoyanov-eisner-2011,
author = "Veselin Stoyanov and Jason Eisner",
title = "Learning Cost-Aware, Loss-Aware Approximate Inference
Policies for Probabilistic Graphical Models",
booktitle = "COST: NeurIPS Workshop on Computational Trade-offs in
Statistical Learning",
note = "5 pages",
year = "2011",
month = dec,
address = "Sierra Nevada, Spain",
URL = "http://cs.jhu.edu/~jason/papers/#stoyanov-eisner-2011",
}

N. Andrews and J. Eisner, “Transformation Process Priors,” in NeurIPS Workshop on Bayesian Nonparametrics: Hope or Hype?, Sierra Nevada, Spain, 2011.
[BibTeX] [Link]

@InProceedings{andrews-eisner-2011,
author = "Nicholas Andrews and Jason Eisner",
title = "Transformation Process Priors",
booktitle = "NeurIPS Workshop on {B}ayesian Nonparametrics: Hope or
Hype?",
note = "Extended abstract (3 pages)",
year = "2011",
month = dec,
address = "Sierra Nevada, Spain",
URL = "http://cs.jhu.edu/~jason/papers/#andrews-eisner-2011",
}

M. R. Gormley, M. Dredze, B. {Van Durme}, and J. Eisner, “Shared Components Topic Models with Application to Selectional Preference,” in NeurIPS Workshop on Learning Semantics, Sierra Nevada, Spain, 2011.
[BibTeX] [Link]

@InProceedings{gormley-et-al-2011,
author = "Matthew R. Gormley and Mark Dredze and Benjamin {Van
Durme} and Jason Eisner",
title = "Shared Components Topic Models with Application to
Selectional Preference",
booktitle = "NeurIPS Workshop on Learning Semantics",
note = "Extended abstract (3 pages)",
year = "2011",
month = dec,
address = "Sierra Nevada, Spain",
URL = "http://cs.jhu.edu/~jason/papers/#gormley-et-al-2011",
}

S. Dura-Bernal, Guillaume Garreau, C. M. Andreou, A. Andreou, J. Georgiou, T. Wennekers, and S. Denham, “Human Action Categorization Using Ultrasound Micro-Doppler Signatures,” in International Workshop on Human Behavior Unterstanding, 2011.
[BibTeX] [Link]

@inproceedings{28206308,
title = {Human Action Categorization Using Ultrasound Micro-Doppler Signatures},
author = {{S. Dura-Bernal} and {Guillaume Garreau} and {C. M. Andreou} and {A. Andreou} and {J. Georgiou} and {T. Wennekers} and {S. Denham}},
year = 2011,
month = {11},
booktitle = {International Workshop on Human Behavior Unterstanding},
url = {https://www.semanticscholar.org/paper/c6afda2d2fa7306af39dd70c5395142daa8694a6},
}

J. Georgiou and A. Andreou, “Guest Editorial – Special Issue on Selected Papers From BioCAS 2010,” in IEEE Trans. Biomed. Circuits Syst., 2011.
[BibTeX] [Link]

@inproceedings{28505411,
title = {Guest Editorial - Special Issue on Selected Papers From BioCAS 2010},
author = {{J. Georgiou} and {A. Andreou}},
year = 2011,
month = {10},
booktitle = {IEEE Trans. Biomed. Circuits Syst.},
url = {https://www.semanticscholar.org/paper/535c18dc7cf4b5ec4484183beca7618f230223c6},
}

M. Dreyer and J. Eisner, “Discovering Morphological Paradigms from Plain Text Using a Dirichlet Process Mixture Model,” in Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Edinburgh, 2011, p. 616–627.
[BibTeX] [Link]

@InProceedings{dreyer-eisner-2011,
aclid = "D11-1057",
author = "Markus Dreyer and Jason Eisner",
title = "Discovering Morphological Paradigms from Plain Text
Using a {D}irichlet Process Mixture Model",
booktitle = "Proceedings of the Conference on Empirical Methods in
Natural Language Processing (EMNLP)",
pages = "616--627",
note = "Supplementary material (9 pages) also available",
year = "2011",
month = jul,
address = "Edinburgh",
URL = "http://cs.jhu.edu/~jason/papers/#dreyer-eisner-2011",
}

Z. Li, J. Eisner, Z. Wang, Sanjeev Khudanpur, and B. Roark, “Minimum Imputed Risk: Unsupervised Discriminative Training for Machine Translation,” in Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Edinburgh, 2011, p. 920–929.
[BibTeX] [Link]

@InProceedings{li-et-al-2011,
aclid = "D11-1085",
author = "Zhifei Li and Jason Eisner and Ziyuan Wang and Sanjeev
Khudanpur and Brian Roark",
title = "Minimum Imputed Risk: Unsupervised Discriminative
Training for Machine Translation",
booktitle = "Proceedings of the Conference on Empirical Methods in
Natural Language Processing (EMNLP)",
pages = "920--929",
year = "2011",
month = jul,
address = "Edinburgh",
URL = "http://cs.jhu.edu/~jason/papers/#li-et-al-2011",
}

C. Parada, M. Dredze, A. Sethy, and A. Rastrow, “Learning Sub-Word Units for Open Vocabulary Speech Recognition,” in Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Portland, Oregon, USA, 2011, p. 712–721.
[BibTeX] [Link]

@inproceedings{parada-etal-2011-learning,
title = "Learning Sub-Word Units for Open Vocabulary Speech Recognition",
author = "Parada, Carolina and
Dredze, Mark and
Sethy, Abhinav and
Rastrow, Ariya",
editor = "Lin, Dekang and
Matsumoto, Yuji and
Mihalcea, Rada",
booktitle = "Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies",
month = jun,
year = "2011",
address = "Portland, Oregon, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P11-1072",
pages = "712--721",
}

V. Stoyanov, A. Ropson, and Jason Eisner, “Empirical Risk Minimization of Graphical Model Parameters Given Approximate Inference, Decoding, and Model Structure,” in Proceedings of the 14th International Conference on Artificial Intelligence and Statistics (AISTATS), Fort Lauderdale, 2011, p. 725–733.
[BibTeX] [Link]

@InProceedings{stoyanov-ropson-eisner-2011,
author = "Veselin Stoyanov and Alexander Ropson and Jason
Eisner",
title = "Empirical Risk Minimization of Graphical Model
Parameters Given Approximate Inference, Decoding, and
Model Structure",
booktitle = "Proceedings of the 14th International Conference on
Artificial Intelligence and Statistics (AISTATS)",
series = "JMLR Workshop and Conference Proceedings",
volume = "15",
pages = "725--733",
note = "Supplementary material (4 pages) also available",
year = "2011",
month = apr,
address = "Fort Lauderdale",
URL = "http://cs.jhu.edu/~jason/papers/#stoyanov-ropson-eisner-2011",
}

Carolina Parada, Mark Dredze, and F. Jelinek, “OOV Sensitive Named-Entity Recognition in Speech,” in Interspeech, 2011.
[BibTeX] [Link]

@inproceedings{15795887,
title = {OOV Sensitive Named-Entity Recognition in Speech},
author = {{Carolina Parada} and {Mark Dredze} and {F. Jelinek}},
year = 2011,
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/21c5073bb8ddf639409a9b01a835053255dbed13},
}

Thomas S. Murray, P. Pouliquen, A. Andreou, and K. Lauritzen, “Design of a CMOS A2I data converter: Theory, architecture and implementation,” in Annual Conference on Information Sciences and Systems, 2011.
[BibTeX] [Link]

@inproceedings{16740428,
title = {Design of a CMOS A2I data converter: Theory, architecture and implementation},
author = {{Thomas S. Murray} and {P. Pouliquen} and {A. Andreou} and {K. Lauritzen}},
year = 2011,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/308e93c9795ec743f30a99506657229f91c56b35},
}

A. Rastrow, Markus Dreyer, A. Sethy, S. Khudanpur, B. Ramabhadran, and Mark Dredze, “Hill climbing on speech lattices: A new rescoring framework,” in IEEE International Conference on Acoustics, Speech, and Signal Processing, 2011.
[BibTeX] [Link]

@inproceedings{8264290,
title = {Hill climbing on speech lattices: A new rescoring framework},
author = {{A. Rastrow} and {Markus Dreyer} and {A. Sethy} and {S. Khudanpur} and {B. Ramabhadran} and {Mark Dredze}},
year = 2011,
month = {5},
booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
url = {https://www.semanticscholar.org/paper/e91558ce4e41d471ea7240b07a96e60b605733b7},
}

A. Andreou, Z. Zhang, R. Ozgun, E. Choi, Z. Kalayjian, M. Marwick, J. Christen, and L. Tung, “Contactless fluorescence imaging with a CMOS image sensor,” in International Symposium on Circuits and Systems, 2011.
[BibTeX] [Link]

@inproceedings{39879224,
title = {Contactless fluorescence imaging with a CMOS image sensor},
author = {{A. Andreou} and {Z. Zhang} and {R. Ozgun} and {E. Choi} and {Z. Kalayjian} and {M. Marwick} and {J. Christen} and {L. Tung}},
year = 2011,
month = {5},
booktitle = {International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/1a0f3f6e745dfd197500b1e483d5e46525059b0a},
}

Joseph H. Lin and A. Andreou, “A 32×32 single photon avalanche diode imager with delay-insensitive address-event readout,” in International Symposium on Circuits and Systems, 2011.
[BibTeX] [Link]

@inproceedings{9193505,
title = {A 32×32 single photon avalanche diode imager with delay-insensitive address-event readout},
author = {{Joseph H. Lin} and {A. Andreou}},
year = 2011,
month = {5},
booktitle = {International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/9635ca6330a305dd9a5d123b9a15642a6b7a8f2d},
}

R. Ozgun, Joseph H. Lin, Francisco Tejada, P. Pouliquen, and A. Andreou, “A low-power 8-bit SAR ADC for a QCIF image sensor,” in International Symposium on Circuits and Systems, 2011.
[BibTeX] [Link]

@inproceedings{10267049,
title = {A low-power 8-bit SAR ADC for a QCIF image sensor},
author = {{R. Ozgun} and {Joseph H. Lin} and {Francisco Tejada} and {P. Pouliquen} and {A. Andreou}},
year = 2011,
month = {5},
booktitle = {International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/01ecb7d577eff81959e48d29c9550231b86ad5b7},
}

A. Cassidy, A. Andreou, and J. Georgiou, “A combinational digital logic approach to STDP,” in International Symposium on Circuits and Systems, 2011.
[BibTeX] [Link]

@inproceedings{19042349,
title = {A combinational digital logic approach to STDP},
author = {{A. Cassidy} and {A. Andreou} and {J. Georgiou}},
year = 2011,
month = {5},
booktitle = {International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/c989515519bbc15483291360839c23df1428ffae},
}

A. Cassidy, A. Andreou, and J. Georgiou, “Design of a one million neuron single FPGA neuromorphic system for real-time multimodal scene analysis,” in Annual Conference on Information Sciences and Systems, 2011.
[BibTeX] [Link]

@inproceedings{14517840,
title = {Design of a one million neuron single FPGA neuromorphic system for real-time multimodal scene analysis},
author = {{A. Cassidy} and {A. Andreou} and {J. Georgiou}},
year = 2011,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/bc7e8ded32d2c4f647276b46e8c6209e0259da2c},
}

A. Cassidy, Kai Yu, Haolang Zhou, and A. Andreou, “A high-level analytical model for application specific CMP design exploration,” in Design, Automation and Test in Europe, 2011.
[BibTeX] [Link]

@inproceedings{14606101,
title = {A high-level analytical model for application specific CMP design exploration},
author = {{A. Cassidy} and {Kai Yu} and {Haolang Zhou} and {A. Andreou}},
year = 2011,
month = {3},
booktitle = {Design, Automation and Test in Europe},
url = {https://www.semanticscholar.org/paper/0087d3f48a3014668dc6da36027c134d9850dc13},
}

Michael J. Paul and Mark Dredze, “A Model for Mining.” 2011.
[BibTeX] [Link]

@inproceedings{7978201,
title = {A Model for Mining},
author = {{Michael J. Paul} and {Mark Dredze}},
year = 2011,
booktitle = {},
url = {https://www.semanticscholar.org/paper/41cbae26fe87307e6878e87b0a08056206a5c4c1},
}

Spence Green, Nicholas Andrews, Matthew R. Gormley, Mark Dredze, and Christopher D. Manning, “Cross-lingual Coreference Resolution : A New Task for Multilingual Comparable Corpora.” 2011.
[BibTeX] [Link]

@inproceedings{15904265,
title = {Cross-lingual Coreference Resolution : A New Task for Multilingual Comparable Corpora},
author = {{Spence Green} and {Nicholas Andrews} and {Matthew R. Gormley} and {Mark Dredze} and {Christopher D. Manning}},
year = 2011,
booktitle = {},
url = {https://www.semanticscholar.org/paper/e91c7d7969a89efc6f2d10504b728fd7d9644f9b},
}

H. Hermansky, Mark Dredze, and Maria Carolina Parada, “Learning sub-word units and exploiting contextual information for open vocabulary speech recognition.” 2011.
[BibTeX] [Link]

@inproceedings{36628046,
title = {Learning sub-word units and exploiting contextual information for open vocabulary speech recognition},
author = {{H. Hermansky} and {Mark Dredze} and {Maria Carolina Parada}},
year = 2011,
booktitle = {},
url = {https://www.semanticscholar.org/paper/0509ca142cb5d3cf11440e29b749d3bbe4b8139b},
}

Joseph H. Lin, P. Pouliquen, A. Andreou, A. Goldberg, and Charbel G. Rizk, “A bio-inspired event-driven digital readout architecture with pixel-level A/D conversion and non-uniformity correction,” in Annual Conference on Information Sciences and Systems, 2011.
[BibTeX] [Link]

@inproceedings{17753471,
title = {A bio-inspired event-driven digital readout architecture with pixel-level A/D conversion and non-uniformity correction},
author = {{Joseph H. Lin} and {P. Pouliquen} and {A. Andreou} and {A. Goldberg} and {Charbel G. Rizk}},
year = 2011,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/f5030491c9cb5ff567f4254cfb9e994651625169},
}

Joseph H. Lin, R. Ozgun, P. Pouliquen, A. Andreou, C. M. Andreou, and J. Georgiou, “A 3-pin 1V 115µW 176×144 autonomous active pixel image sensor in 0.18µm CMOS,” in International Symposium on Circuits and Systems, 2011.
[BibTeX] [Link]

@inproceedings{30336890,
title = {A 3-pin 1V 115µW 176×144 autonomous active pixel image sensor in 0.18µm CMOS},
author = {{Joseph H. Lin} and {R. Ozgun} and {P. Pouliquen} and {A. Andreou} and {C. M. Andreou} and {J. Georgiou}},
year = 2011,
month = {5},
booktitle = {International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/09440eca3b48bd93d3c65bd1bc220d26e38c08be},
}

J. Georgiou, P. Pouliquen, A. Cassidy, Guillaume Garreau, C. M. Andreou, G. Stuarts, Cyrille d’Urbal, A. Andreou, S. Denham, T. Wennekers, R. Mill, I. Winkler, Tamás Bohm, O. Szalárdy, G. Klump, Simon J. Jones, and A. Bendixen, “A multimodal-corpus data collection system for cognitive acoustic scene analysis,” in Annual Conference on Information Sciences and Systems, 2011.
[BibTeX] [Link]

@inproceedings{646791,
title = {A multimodal-corpus data collection system for cognitive acoustic scene analysis},
author = {{J. Georgiou} and {P. Pouliquen} and {A. Cassidy} and {Guillaume Garreau} and {C. M. Andreou} and {G. Stuarts} and {Cyrille d'Urbal} and {A. Andreou} and {S. Denham} and {T. Wennekers} and {R. Mill} and {I. Winkler} and {Tamás Bohm} and {O. Szalárdy} and {G. Klump} and {Simon J. Jones} and {A. Bendixen}},
year = 2011,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/311d0fa5b9d9e40d195843c1540884857226eb40},
}

B. Dhar, R. Ozgun, Thomas J. Dawidczyk, A. Andreou, and H. Katz, “Threshold voltage shifting for memory and tuning in printed transistor circuits,” in Materials Science & Engineering R-reports, 2011.
[BibTeX] [Link]

@inproceedings{111276948,
title = {Threshold voltage shifting for memory and tuning in printed transistor circuits},
author = {{B. Dhar} and {R. Ozgun} and {Thomas J. Dawidczyk} and {A. Andreou} and {H. Katz}},
year = 2011,
month = {5},
booktitle = {Materials Science & Engineering R-reports},
url = {https://www.semanticscholar.org/paper/0deb3ecc444e81c8a44b2ae5441ed372a865bb20},
}

Michael J. Paul and Mark Dredze, “You Are What You Tweet: Analyzing Twitter for Public Health,” in International Conference on Web and Social Media, 2011.
[BibTeX] [Link]

@inproceedings{9270435,
title = {You Are What You Tweet: Analyzing Twitter for Public Health},
author = {{Michael J. Paul} and {Mark Dredze}},
year = 2011,
month = {7},
booktitle = {International Conference on Web and Social Media},
url = {https://www.semanticscholar.org/paper/e4e3d5552a0071f4f677d06c672c31b402b1266c},
}

R. Ozgun, Byung-Jun Jung, B. Dhar, H. Katz, and A. Andreou, “Silicon-on-insulator (SOI) integration for organic field effect transistor (OFET) based circuits,” in International Symposium on Circuits and Systems, 2011.
[BibTeX] [Link]

@inproceedings{12238735,
title = {Silicon-on-insulator (SOI) integration for organic field effect transistor (OFET) based circuits},
author = {{R. Ozgun} and {Byung-Jun Jung} and {B. Dhar} and {H. Katz} and {A. Andreou}},
year = 2011,
month = {5},
booktitle = {International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/791b977f734aa819478749a5e7791bc94bb4c093},
}

J. Georgiou, P. Pouliquen, A. Cassidy, Guillaume Garreau, C. M. Andreou, G. Stuarts, Cyrille d’Urbal, A. Andreou, S. Denham, T. Wennekers, R. Mill, G. Klump, Simon J. Jones, I. Winkler, Tamás Bohm, O. Szalárdy, and A. Bendixen, “for Cognitive Acoustic Scene Analysis.” 2011.
[BibTeX] [Link]

@inproceedings{110542813,
title = {for Cognitive Acoustic Scene Analysis},
author = {{J. Georgiou} and {P. Pouliquen} and {A. Cassidy} and {Guillaume Garreau} and {C. M. Andreou} and {G. Stuarts} and {Cyrille d'Urbal} and {A. Andreou} and {S. Denham} and {T. Wennekers} and {R. Mill} and {G. Klump} and {Simon J. Jones} and {I. Winkler} and {Tamás Bohm} and {O. Szalárdy} and {A. Bendixen}},
year = 2011,
booktitle = {},
url = {https://www.semanticscholar.org/paper/e3d95f53a481897bffc003e76abec8f2e0d0b25f},
}

A. Cassidy, Thomas S. Murray, A. Andreou, and J. Georgiou, “Evaluating on-chip interconnects for low operating frequency silicon neuron arrays,” in International Symposium on Circuits and Systems, 2011.
[BibTeX] [Link]

@inproceedings{20185260,
title = {Evaluating on-chip interconnects for low operating frequency silicon neuron arrays},
author = {{A. Cassidy} and {Thomas S. Murray} and {A. Andreou} and {J. Georgiou}},
year = 2011,
month = {5},
booktitle = {International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/85446bccf2ba8dfa48f8a762fc717a744bc2604b},
}

P. Pouliquen, A. Cassidy, A. Andreou, Guillaume Garreau, and J. Georgiou, “A wireless architecture for distributed sensing/actuation and pre-processing with microsecond synchronization,” in Annual Conference on Information Sciences and Systems, 2011.
[BibTeX] [Link]

@inproceedings{1462340,
title = {A wireless architecture for distributed sensing/actuation and pre-processing with microsecond synchronization},
author = {{P. Pouliquen} and {A. Cassidy} and {A. Andreou} and {Guillaume Garreau} and {J. Georgiou}},
year = 2011,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/1501b6884fd95804d80e81b8381963693a1d31c2},
}

Andre Harrison, R. Ozgun, Joseph H. Lin, A. Andreou, and R. Etienne-Cummings, “A spike based 3D imager chip using a mixed mode encoding readout,” in Biomedical Circuits and Systems Conference, 2010.
[BibTeX] [Link]

@inproceedings{35894994,
title = {A spike based 3D imager chip using a mixed mode encoding readout},
author = {{Andre Harrison} and {R. Ozgun} and {Joseph H. Lin} and {A. Andreou} and {R. Etienne-Cummings}},
year = 2010,
month = {11},
booktitle = {Biomedical Circuits and Systems Conference},
url = {https://www.semanticscholar.org/paper/0371f6816c8478fc69b80e2c766718d12959db5f},
}

M. Dredze, T. Oates, and C. Piatko, “We’re Not in Kansas Anymore: Detecting Domain Changes in Streams,” in Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, Cambridge, MA, 2010, p. 585–595.
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@inproceedings{dredze-etal-2010-kansas,
title = "We{'}re Not in {K}ansas Anymore: Detecting Domain Changes in Streams",
author = "Dredze, Mark and
Oates, Tim and
Piatko, Christine",
editor = "Li, Hang and
M{\`a}rquez, Llu{\'\i}s",
booktitle = "Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing",
month = oct,
year = "2010",
address = "Cambridge, MA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D10-1057",
pages = "585--595",
}

M. Dredze, A. Jansen, G. Coppersmith, and K. Church, “NLP on Spoken Documents Without ASR,” in Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, Cambridge, MA, 2010, p. 460–470.
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@inproceedings{dredze-etal-2010-nlp,
title = "{NLP} on Spoken Documents Without {ASR}",
author = "Dredze, Mark and
Jansen, Aren and
Coppersmith, Glen and
Church, Ken",
editor = "Li, Hang and
M{\`a}rquez, Llu{\'\i}s",
booktitle = "Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing",
month = oct,
year = "2010",
address = "Cambridge, MA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D10-1045",
pages = "460--470",
}

J. A. Rodriguez, P. Julián, and A. Andreou, “Frame and arithmetic pipelining for a radix-4 FFT streamed core,” in Argentine School of Micro-Nanoelectronics, Technology and Applications, 2010.
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@inproceedings{17257760,
title = {Frame and arithmetic pipelining for a radix-4 FFT streamed core},
author = {{J. A. Rodriguez} and {P. Julián} and {A. Andreou}},
year = 2010,
month = {10},
booktitle = {Argentine School of Micro-Nanoelectronics, Technology and Applications},
url = {https://www.semanticscholar.org/paper/ef0d9f52109e7382b7a276b2930566ee25bb0204},
}

M. Dredze, P. McNamee, D. Rao, A. Gerber, and T. Finin, “Entity Disambiguation for Knowledge Base Population,” in Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010), Beijing, China, 2010, p. 277–285.
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@inproceedings{dredze-etal-2010-entity,
title = "Entity Disambiguation for Knowledge Base Population",
author = "Dredze, Mark and
McNamee, Paul and
Rao, Delip and
Gerber, Adam and
Finin, Tim",
editor = "Huang, Chu-Ren and
Jurafsky, Dan",
booktitle = "Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010)",
month = aug,
year = "2010",
address = "Beijing, China",
publisher = "Coling 2010 Organizing Committee",
url = "https://aclanthology.org/C10-1032",
pages = "277--285",
}

D. Rao, P. McNamee, and M. Dredze, “Streaming Cross Document Entity Coreference Resolution,” in Coling 2010: Posters, Beijing, China, 2010, p. 1050–1058.
[BibTeX] [Link]

@inproceedings{rao-etal-2010-streaming,
title = "Streaming Cross Document Entity Coreference Resolution",
author = "Rao, Delip and
McNamee, Paul and
Dredze, Mark",
editor = "Huang, Chu-Ren and
Jurafsky, Dan",
booktitle = "Coling 2010: Posters",
month = aug,
year = "2010",
address = "Beijing, China",
publisher = "Coling 2010 Organizing Committee",
url = "https://aclanthology.org/C10-2121",
pages = "1050--1058",
}

Z. Li, Z. Wang, S. Khudanpur, and J. Eisner, “Unsupervised Discriminative Language Model Training for Machine Translation using Simulated Confusion Sets,” in Proceedings of the 23rd International Conference on Computational Linguistics (COLING), Beijing, 2010, p. 656–664.
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@InProceedings{li-et-al-2010,
aclid = "C10-2075",
author = "Zhifei Li and Ziyuan Wang and Sanjeev Khudanpur and
Jason Eisner",
title = "Unsupervised Discriminative Language Model Training
for Machine Translation using Simulated Confusion
Sets",
booktitle = "Proceedings of the 23rd International Conference on
Computational Linguistics (COLING)",
pages = "656--664",
year = "2010",
month = aug,
address = "Beijing",
URL = "http://cs.jhu.edu/~jason/papers/#li-et-al-2010",
}

M. R. Gormley, A. Gerber, M. Harper, and M. Dredze, “Non-Expert Correction of Automatically Generated Relation Annotations,” in Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon’s Mechanical Turk, Los Angeles, 2010, p. 204–207.
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@inproceedings{gormley-etal-2010-non,
title = "Non-Expert Correction of Automatically Generated Relation Annotations",
author = "Gormley, Matthew R. and
Gerber, Adam and
Harper, Mary and
Dredze, Mark",
editor = "Callison-Burch, Chris and
Dredze, Mark",
booktitle = "Proceedings of the {NAACL} {HLT} 2010 Workshop on Creating Speech and Language Data with {A}mazon{'}s Mechanical Turk",
month = jun,
year = "2010",
address = "Los Angeles",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W10-0732",
pages = "204--207",
}

C. Parada, M. Dredze, D. Filimonov, and F. Jelinek, “Contextual Information Improves OOV Detection in Speech,” in Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Los Angeles, California, 2010, p. 216–224.
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@inproceedings{parada-etal-2010-contextual,
title = "Contextual Information Improves {OOV} Detection in Speech",
author = "Parada, Carolina and
Dredze, Mark and
Filimonov, Denis and
Jelinek, Frederick",
editor = "Kaplan, Ron and
Burstein, Jill and
Harper, Mary and
Penn, Gerald",
booktitle = "Human Language Technologies: The 2010 Annual Conference of the North {A}merican Chapter of the Association for Computational Linguistics",
month = jun,
year = "2010",
address = "Los Angeles, California",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N10-1025",
pages = "216--224",
}

T. Finin, W. Murnane, A. Karandikar, N. Keller, J. Martineau, and M. Dredze, “Annotating Named Entities in Twitter Data with Crowdsourcing,” in Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon’s Mechanical Turk, Los Angeles, 2010, p. 80–88.
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@inproceedings{finin-etal-2010-annotating,
title = "Annotating Named Entities in {T}witter Data with Crowdsourcing",
author = "Finin, Tim and
Murnane, William and
Karandikar, Anand and
Keller, Nicholas and
Martineau, Justin and
Dredze, Mark",
editor = "Callison-Burch, Chris and
Dredze, Mark",
booktitle = "Proceedings of the {NAACL} {HLT} 2010 Workshop on Creating Speech and Language Data with {A}mazon{'}s Mechanical Turk",
month = jun,
year = "2010",
address = "Los Angeles",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W10-0713",
pages = "80--88",
}

C. Napoles and M. Dredze, “Learning Simple Wikipedia: A Cogitation in Ascertaining Abecedarian Language,” in Proceedings of the NAACL HLT 2010 Workshop on Computational Linguistics and Writing: Writing Processes and Authoring Aids, Los Angeles, CA, USA, 2010, p. 42–50.
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@inproceedings{napoles-dredze-2010-learning,
title = "Learning {S}imple {W}ikipedia: A Cogitation in Ascertaining Abecedarian Language",
author = "Napoles, Courtney and
Dredze, Mark",
editor = "Piotrowski, Michael and
Mahlow, Cerstin and
Dale, Robert",
booktitle = "Proceedings of the {NAACL} {HLT} 2010 Workshop on Computational Linguistics and Writing: Writing Processes and Authoring Aids",
month = jun,
year = "2010",
address = "Los Angeles, CA, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W10-0406",
pages = "42--50",
}

Mark Dredze, Alex Kulesza, and K. Crammer, “Multi-domain learning by confidence-weighted parameter combination,” in Machine-mediated learning, 2010.
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@inproceedings{7822049,
title = {Multi-domain learning by confidence-weighted parameter combination},
author = {{Mark Dredze} and {Alex Kulesza} and {K. Crammer}},
year = 2010,
month = {5},
booktitle = {Machine-mediated learning},
url = {https://www.semanticscholar.org/paper/5959ca92fe68e5c06fa4feedc32d9a94d1b2c03a},
}

A. Andreou and A. Cassidy, “Three topics in single-chip parallel computing: theoretical foundations, speech recognition, and the silicon cortex.” 2010.
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@inproceedings{65076078,
title = {Three topics in single-chip parallel computing: theoretical foundations, speech recognition, and the silicon cortex},
author = {{A. Andreou} and {A. Cassidy}},
year = 2010,
booktitle = {},
url = {https://www.semanticscholar.org/paper/1acb073706f67208f9188ebe68285303079ac073},
}

Chris Callison-Burch and Mark Dredze, “Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon’s Mechanical Turk.” 2010.
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@inproceedings{12295680,
title = {Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon's Mechanical Turk},
author = {{Chris Callison-Burch} and {Mark Dredze}},
year = 2010,
month = {6},
booktitle = {},
url = {https://www.semanticscholar.org/paper/e79470389fe3f73d37e8fc099439cd17e1c7748d},
}

Damianos G. Karakos, Haolang Zhou, Puyang Xu, S. Khudanpur, and A. Andreou, “Two Self-supervised Learning Techniques for Speech Recognition.” 2010.
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@inproceedings{14073180,
title = {Two Self-supervised Learning Techniques for Speech Recognition},
author = {{Damianos G. Karakos} and {Haolang Zhou} and {Puyang Xu} and {S. Khudanpur} and {A. Andreou}},
year = 2010,
booktitle = {},
url = {https://www.semanticscholar.org/paper/59e9355329b0418f99608a9d5c615963bcd495f1},
}

Carolina Parada, A. Sethy, Mark Dredze, and F. Jelinek, “A spoken term detection framework for recovering out-of-vocabulary words using the web,” in Interspeech, 2010.
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@inproceedings{1023659,
title = {A spoken term detection framework for recovering out-of-vocabulary words using the web},
author = {{Carolina Parada} and {A. Sethy} and {Mark Dredze} and {F. Jelinek}},
year = 2010,
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/c936ae825c7d6acd856d935564db78a455016e40},
}

Byung-Jun Jung, Kyu-Chul Lee, Jia Sun, A. Andreou, and H. Katz, “Air‐Operable, High‐Mobility Organic Transistors with Semifluorinated Side Chains and Unsubstituted Naphthalenetetracarboxylic Diimide Cores: High Mobility and Environmental and Bias Stress Stability from the Perfluorooctylpropyl Side Chain,” in Advanced Functional Materials, 2010.
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@inproceedings{94175074,
title = {Air‐Operable, High‐Mobility Organic Transistors with Semifluorinated Side Chains and Unsubstituted Naphthalenetetracarboxylic Diimide Cores: High Mobility and Environmental and Bias Stress Stability from the Perfluorooctylpropyl Side Chain},
author = {{Byung-Jun Jung} and {Kyu-Chul Lee} and {Jia Sun} and {A. Andreou} and {H. Katz}},
year = 2010,
month = {9},
booktitle = {Advanced Functional Materials},
url = {https://www.semanticscholar.org/paper/ab3af82be39b3bd0a9b7685ecb6121e1fb42596e},
}

M. D. Federico, P. Julián, P. Mandolesi, and A. Andreou, “PWL cores for nonlinear array processing,” in Proceedings of 2010 IEEE International Symposium on Circuits and Systems, 2010.
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@inproceedings{19277242,
title = {PWL cores for nonlinear array processing},
author = {{M. D. Federico} and {P. Julián} and {P. Mandolesi} and {A. Andreou}},
year = 2010,
month = {8},
booktitle = {Proceedings of 2010 IEEE International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/3d1a3da98efd49701de9f25898812b663250f8af},
}

Charbel G. Rizk, P. Pouliquen, and A. Andreou, “Flexible Readout and Integration Sensor (FRIS): New Class of Imaging Sensor Arrays Optimized for Air and Missile Defense,” in Johns Hopkins Apl Technical Digest, 2010.
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@inproceedings{16064355,
title = {Flexible Readout and Integration Sensor (FRIS): New Class of Imaging Sensor Arrays Optimized for Air and Missile Defense},
author = {{Charbel G. Rizk} and {P. Pouliquen} and {A. Andreou}},
year = 2010,
booktitle = {Johns Hopkins Apl Technical Digest},
url = {https://www.semanticscholar.org/paper/8e20e16338c79dddcab19c1afd95c1fd30d7dfcf},
}

B. Dhar, R. Ozgun, Byung-Jun Jung, H. Katz, and A. Andreou, “Optimum bias of CMOS organic field effect transistor inverter through threshold adjustment of both p- and n-type devices,” in Electronics Letters, 2010.
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@inproceedings{109435897,
title = {Optimum bias of CMOS organic field effect transistor inverter through threshold adjustment of both p- and n-type devices},
author = {{B. Dhar} and {R. Ozgun} and {Byung-Jun Jung} and {H. Katz} and {A. Andreou}},
year = 2010,
month = {9},
booktitle = {Electronics Letters},
url = {https://www.semanticscholar.org/paper/8f9b6992e3a852b739d2612646f07940b7e0ed33},
}

Justin Ma, Alex Kulesza, Mark Dredze, K. Crammer, L. Saul, and Fernando C Pereira, “Exploiting Feature Covariance in High-Dimensional Online Learning,” in International Conference on Artificial Intelligence and Statistics, 2010.
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@inproceedings{14129598,
title = {Exploiting Feature Covariance in High-Dimensional Online Learning},
author = {{Justin Ma} and {Alex Kulesza} and {Mark Dredze} and {K. Crammer} and {L. Saul} and {Fernando C Pereira}},
year = 2010,
month = {3},
booktitle = {International Conference on Artificial Intelligence and Statistics},
url = {https://www.semanticscholar.org/paper/6b5061fbbe1727c0dabbbed48012cbfac7e255c9},
}

H. Korth, K. Strohbehn, Francisco Tejada, A. Andreou, S. Mcveigh, J. Kitching, and S. Knappe, “Chip-Scale Absolute Scalar Magnetometer for Space Applications,” in Johns Hopkins Apl Technical Digest, 2010.
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@inproceedings{124482575,
title = {Chip-Scale Absolute Scalar Magnetometer for Space Applications},
author = {{H. Korth} and {K. Strohbehn} and {Francisco Tejada} and {A. Andreou} and {S. Mcveigh} and {J. Kitching} and {S. Knappe}},
year = 2010,
booktitle = {Johns Hopkins Apl Technical Digest},
url = {https://www.semanticscholar.org/paper/70af5c414fda1d60416d275e8ab73837306a652f},
}

Paul McNamee, Mark Dredze, Adam Gerber, Nikesh Garera, Timothy W. Finin, J. Mayfield, C. Piatko, D. Rao, David Yarowsky, and Markus Dreyer, “HLTCOE Approaches to Knowledge Base Population at TAC 2009,” in Text Analysis Conference, 2009.
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@inproceedings{1067273,
title = {HLTCOE Approaches to Knowledge Base Population at TAC 2009},
author = {{Paul McNamee} and {Mark Dredze} and {Adam Gerber} and {Nikesh Garera} and {Timothy W. Finin} and {J. Mayfield} and {C. Piatko} and {D. Rao} and {David Yarowsky} and {Markus Dreyer}},
year = 2009,
month = {11},
booktitle = {Text Analysis Conference},
url = {https://www.semanticscholar.org/paper/35cbf98266b94d7d31d67e09faf57f8ea6f2204f},
}

K. Crammer, M. Dredze, and A. Kulesza, “Multi-Class Confidence Weighted Algorithms,” in Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, Singapore, 2009, p. 496–504.
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@inproceedings{crammer-etal-2009-multi,
title = "Multi-Class Confidence Weighted Algorithms",
author = "Crammer, Koby and
Dredze, Mark and
Kulesza, Alex",
editor = "Koehn, Philipp and
Mihalcea, Rada",
booktitle = "Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing",
month = aug,
year = "2009",
address = "Singapore",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D09-1052",
pages = "496--504",
}

Z. Li and J. Eisner, “First- and Second-Order Expectation Semirings with Applications to Minimum-Risk Training on Translation Forests,” in Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Singapore, 2009, p. 40–51.
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@InProceedings{li-eisner-2009,
aclid = "D09-1005",
author = "Zhifei Li and Jason Eisner",
title = "First- and Second-Order Expectation Semirings with
Applications to Minimum-Risk Training on Translation
Forests",
booktitle = "Proceedings of the Conference on Empirical Methods in
Natural Language Processing (EMNLP)",
pages = "40--51",
year = "2009",
month = aug,
address = "Singapore",
URL = "http://cs.jhu.edu/~jason/papers/#li-eisner-2009",
}

M. Dreyer and J. Eisner, “Graphical Models over Multiple Strings,” in Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Singapore, 2009, p. 101–110.
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@InProceedings{dreyer-eisner-2009,
aclid = "D09-1011",
author = "Markus Dreyer and Jason Eisner",
title = "Graphical Models over Multiple Strings",
booktitle = "Proceedings of the Conference on Empirical Methods in
Natural Language Processing (EMNLP)",
pages = "101--110",
year = "2009",
month = aug,
address = "Singapore",
URL = "http://cs.jhu.edu/~jason/papers/#dreyer-eisner-2009",
}

D. A. Smith and J. Eisner, “Parser Adaptation and Projection with Quasi-Synchronous Grammar Features,” in Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Singapore, 2009, p. 822–831.
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@InProceedings{smith-eisner-2009,
aclid = "D09-1086",
author = "David A. Smith and Jason Eisner",
title = "Parser Adaptation and Projection with
Quasi-Synchronous Grammar Features",
booktitle = "Proceedings of the Conference on Empirical Methods in
Natural Language Processing (EMNLP)",
pages = "822--831",
year = "2009",
month = aug,
address = "Singapore",
URL = "http://cs.jhu.edu/~jason/papers/#smith-eisner-2009",
}

R. Tromble and J. Eisner, “Learning Linear Ordering Problems for Better Translation,” in Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Singapore, 2009, p. 1007–1016.
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@InProceedings{tromble-eisner-2009,
aclid = "D09-1105",
author = "Roy Tromble and Jason Eisner",
title = "Learning Linear Ordering Problems for Better
Translation",
booktitle = "Proceedings of the Conference on Empirical Methods in
Natural Language Processing (EMNLP)",
pages = "1007--1016",
year = "2009",
month = aug,
address = "Singapore",
URL = "http://cs.jhu.edu/~jason/papers/#tromble-eisner-2009",
}

Z. Li, J. Eisner, and S. Khudanpur, “Variational Decoding for Statistical Machine Translation,” in Proceedings of the 47th Annual Meeting of the Association for Computational Linguistics (ACL), Singapore, 2009, p. 593–601.
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@InProceedings{li-eisner-khudanpur-2009,
aclid = "P09-1067",
author = "Zhifei Li and Jason Eisner and Sanjeev Khudanpur",
title = "Variational Decoding for Statistical Machine
Translation",
booktitle = "Proceedings of the 47th Annual Meeting of the
Association for Computational Linguistics (ACL)",
pages = "593--601",
year = "2009",
month = aug,
address = "Singapore",
note = "Nominated for Best Paper Award.",
URL = "http://cs.jhu.edu/~jason/papers/#li-eisner-khudanpur-2009",
}

J. Mayfield, D. Alexander, B. Dorr, J. Eisner, T. Elsayed, T. Finin, Clay Fink, M. Freedman, N. Garera, Paul McNamee, S. Mohammad, D. Oard, C. Piatko, A. Sayeed, Z. Syed, R. Weischedel, T. Xu, and D. Yarowsky, “Cross-Document Coreference Resolution: A Key Technology for Learning by Reading,” in Proceedings of the AAAI 2009 Spring Symposium on Learning by Reading and Learning to Read, Stanford, 2009.
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@InProceedings{mayfield-et-al-2009,
author = "James Mayfield and David Alexander and Bonnie Dorr and
Jason Eisner and Tamer Elsayed and Tim Finin and Clay
Fink and Marjorie Freedman and Nikesh Garera and Paul
McNamee and Saif Mohammad and Douglas Oard and
Christine Piatko and Asad Sayeed and Zareen Syed and
Ralph Weischedel and Tan Xu and David Yarowsky",
title = "Cross-Document Coreference Resolution: {A} Key
Technology for Learning by Reading",
booktitle = "Proceedings of the AAAI 2009 Spring Symposium on
Learning by Reading and Learning to Read",
year = "2009",
month = mar,
address = "Stanford",
note = "AAAI Technical Report SS-09-07",
URL = "http://cs.jhu.edu/~jason/papers/#mayfield-et-al-2009",
}

Razvan C. Bunescu, Vitor R. Carvalho, J. Chomicki, Vincent Conitzer, Michael T. Cox, Virginia Dignum, Z. Dodds, Mark Dredze, David Furcy, E. Gabrilovich, M. Göker, H. Guesgen, H. Hirsh, D. Jannach, Ulrich Junker, W. Ketter, A. Kobsa, Sven Koenig, T. Lau, Lundy M. Lewis, E. Matson, Ted Metzler, Rada Mihalcea, B. Mobasher, Joelle Pineau, P. Poupart, A. Raja, Wheeler Ruml, N. Sadeh, Guy Shani, D. Shapiro, S. Anand, Matthew E. Taylor, K. Wagstaff, Trey Smith, W. E. Walsh, and R. Zhou, “AAAI 2008 Workshop Reports,” in The AI Magazine, 2009.
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@inproceedings{7218649,
title = {AAAI 2008 Workshop Reports},
author = {{Razvan C. Bunescu} and {Vitor R. Carvalho} and {J. Chomicki} and {Vincent Conitzer} and {Michael T. Cox} and {Virginia Dignum} and {Z. Dodds} and {Mark Dredze} and {David Furcy} and {E. Gabrilovich} and {M. Göker} and {H. Guesgen} and {H. Hirsh} and {D. Jannach} and {Ulrich Junker} and {W. Ketter} and {A. Kobsa} and {Sven Koenig} and {T. Lau} and {Lundy M. Lewis} and {E. Matson} and {Ted Metzler} and {Rada Mihalcea} and {B. Mobasher} and {Joelle Pineau} and {P. Poupart} and {A. Raja} and {Wheeler Ruml} and {N. Sadeh} and {Guy Shani} and {D. Shapiro} and {S. Anand} and {Matthew E. Taylor} and {K. Wagstaff} and {Trey Smith} and {W. E. Walsh} and {R. Zhou}},
year = 2009,
month = {1},
booktitle = {The AI Magazine},
url = {https://www.semanticscholar.org/paper/103cfa1847ac1d1d7212c0dfb7f2c3f85e570dad},
}

A. Andreou, P. Pouliquen, and Charbel G. Rizk, “Noise analysis and comparison of analog and digital readout integrated circuits for infrared focal plane arrays,” in Annual Conference on Information Sciences and Systems, 2009.
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@inproceedings{18660239,
title = {Noise analysis and comparison of analog and digital readout integrated circuits for infrared focal plane arrays},
author = {{A. Andreou} and {P. Pouliquen} and {Charbel G. Rizk}},
year = 2009,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/c0c63f21b5bee5e7424029f2ef7a2e7934e60d05},
}

Edward Choi and A. Andreou, “Architecture of a , uRFID with integrated antenna in.” 2009.
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@inproceedings{17100540,
title = {Architecture of a , uRFID with integrated antenna in},
author = {{Edward Choi} and {A. Andreou}},
year = 2009,
booktitle = {},
url = {https://www.semanticscholar.org/paper/9e11d3a65c90f6b54b7fab2adfaf6b11609e5de7},
}

Haolang Zhou, Damianos G. Karakos, S. Khudanpur, A. Andreou, and C. Priebe, “On projections of Gaussian distributions using maximum likelihood criteria,” in Information Theory and Applications Workshop, 2009.
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@inproceedings{8642318,
title = {On projections of Gaussian distributions using maximum likelihood criteria},
author = {{Haolang Zhou} and {Damianos G. Karakos} and {S. Khudanpur} and {A. Andreou} and {C. Priebe}},
year = 2009,
month = {5},
booktitle = {Information Theory and Applications Workshop},
url = {https://www.semanticscholar.org/paper/05b75a1b51a4a0b387d4a3d51ce322cf0116bad1},
}

Mark Dredze, P. Talukdar, and K. Crammer, “Sequence Learning from Data with Multiple Labels.” 2009.
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@inproceedings{1707818,
title = {Sequence Learning from Data with Multiple Labels},
author = {{Mark Dredze} and {P. Talukdar} and {K. Crammer}},
year = 2009,
booktitle = {},
url = {https://www.semanticscholar.org/paper/893107da9d13f0abb8c66cd351d056990a94674a},
}

F. Folowosele, Andre Harrison, A. Cassidy, A. Andreou, R. Etienne-Cummings, Stefan Mihalas, E. Niebur, and T. Hamilton, “A switched capacitor implementation of the generalized linear integrate-and-fire neuron,” in 2009 IEEE International Symposium on Circuits and Systems, 2009.
[BibTeX] [Link]

@inproceedings{11825117,
title = {A switched capacitor implementation of the generalized linear integrate-and-fire neuron},
author = {{F. Folowosele} and {Andre Harrison} and {A. Cassidy} and {A. Andreou} and {R. Etienne-Cummings} and {Stefan Mihalas} and {E. Niebur} and {T. Hamilton}},
year = 2009,
month = {5},
booktitle = {2009 IEEE International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/2e323100e5216dd5d5afa9145af469f06d28da49},
}

D. Allstot, D. B. Fogel, T. Lande, R. Butera, A. Andreou, A. Bermak, S. Carrara, G. Cauwenberghs, K. Chakrabarty, K. Cheung, T. Delbruck, S. DeWeerth, G. Inst, E. Drakakis, David Cumming, Sanqing Hu, E. Jovanov, E. Lam, Yong Lian, P. Mohseni, R. Rieger, R. Sarpeshkar, M. Sawan, T. Roska, and Zhihua Wang, “Engineering in Medicine and Biology B. HE, President TECHNICAL CO-SPONSORING SOCIETIES Computational Intelligence.” 2009.
[BibTeX] [Link]

@inproceedings{110878060,
title = {Engineering in Medicine and Biology B. HE, President TECHNICAL CO-SPONSORING SOCIETIES Computational Intelligence},
author = {{D. Allstot} and {D. B. Fogel} and {T. Lande} and {R. Butera} and {A. Andreou} and {A. Bermak} and {S. Carrara} and {G. Cauwenberghs} and {K. Chakrabarty} and {K. Cheung} and {T. Delbruck} and {S. DeWeerth} and {G. Inst} and {E. Drakakis} and {David Cumming} and {Sanqing Hu} and {E. Jovanov} and {E. Lam} and {Yong Lian} and {P. Mohseni} and {R. Rieger} and {R. Sarpeshkar} and {M. Sawan} and {T. Roska} and {Zhihua Wang}},
year = 2009,
booktitle = {},
url = {https://www.semanticscholar.org/paper/a637178daae0eb5df98e1c29f6dce424d184cb62},
}

Mark Dredze, Bill N. Schilit, and Peter Norvig, “Suggesting Email View Filters for Triage and Search,” in International Joint Conference on Artificial Intelligence, 2009.
[BibTeX] [Link]

@inproceedings{59819689,
title = {Suggesting Email View Filters for Triage and Search},
author = {{Mark Dredze} and {Bill N. Schilit} and {Peter Norvig}},
year = 2009,
month = {7},
booktitle = {International Joint Conference on Artificial Intelligence},
url = {https://www.semanticscholar.org/paper/c9ac7e404b5b7bbbb303ad8c3c2994541cbf2406},
}

Haolang Zhou, Damianos G. Karakos, and A. Andreou, “A semi-supervised version of heteroscedastic linear discriminant analysis,” in Interspeech, 2009.
[BibTeX] [Link]

@inproceedings{373380,
title = {A semi-supervised version of heteroscedastic linear discriminant analysis},
author = {{Haolang Zhou} and {Damianos G. Karakos} and {A. Andreou}},
year = 2009,
booktitle = {Interspeech},
url = {https://www.semanticscholar.org/paper/b761a86352d9ea83ea0e6e92f15a448e4eadab2f},
}

A. Cassidy and A. Andreou, “Analytical methods for the design and optimization of chip-multiprocessor architectures,” in Annual Conference on Information Sciences and Systems, 2009.
[BibTeX] [Link]

@inproceedings{2658030,
title = {Analytical methods for the design and optimization of chip-multiprocessor architectures},
author = {{A. Cassidy} and {A. Andreou}},
year = 2009,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/ea36a5199bd647d96ca193cc577f7a5033414e6b},
}

O. F. Zaidan, J. Eisner, and C. Piatko, “Machine Learning with Annotator Rationales to Reduce Annotation Cost,” in Proceedings of the NeurIPS*2008 Workshop on Cost Sensitive Learning, Whistler, BC, 2008.
[BibTeX] [Link]

@InProceedings{zaidan-eisner-piatko-2008,
author = "Omar F. Zaidan and Jason Eisner and Christine Piatko",
title = "Machine Learning with Annotator Rationales to Reduce
Annotation Cost",
booktitle = "Proceedings of the NeurIPS*2008 Workshop on Cost
Sensitive Learning",
note = "10 pages",
year = "2008",
month = dec,
address = "Whistler, BC",
URL = "http://cs.jhu.edu/~jason/papers/#zaidan-eisner-piatko-2008",
}

A. Cassidy and A. Andreou, “Dynamical digital silicon neurons,” in 2008 IEEE Biomedical Circuits and Systems Conference, 2008.
[BibTeX] [Link]

@inproceedings{1623171,
title = {Dynamical digital silicon neurons},
author = {{A. Cassidy} and {A. Andreou}},
year = 2008,
month = {11},
booktitle = {2008 IEEE Biomedical Circuits and Systems Conference},
url = {https://www.semanticscholar.org/paper/057ed292b9a95b1bf6efc8b22cfe55d0a266dafe},
}

A. Cassidy, Z. Zhang, and A. Andreou, “Neuromorphic interconnects using Ultra Wideband radio,” in 2008 IEEE Biomedical Circuits and Systems Conference, 2008.
[BibTeX] [Link]

@inproceedings{6024302,
title = {Neuromorphic interconnects using Ultra Wideband radio},
author = {{A. Cassidy} and {Z. Zhang} and {A. Andreou}},
year = 2008,
month = {11},
booktitle = {2008 IEEE Biomedical Circuits and Systems Conference},
url = {https://www.semanticscholar.org/paper/fbe9895986a4cad7fef4848d2d46eeb45d3dc9e4},
}

E. Choi, R. Ozgun, B. Dhar, H. Katz, and A. Andreou, “Fabrication process design for complementary metal-cytop-organic-semiconductor integrated circuits,” in Argentine School of Micro-Nanoelectronics, Technology and Applications, 2008.
[BibTeX] [Link]

@inproceedings{15697569,
title = {Fabrication process design for complementary metal-cytop-organic-semiconductor integrated circuits},
author = {{E. Choi} and {R. Ozgun} and {B. Dhar} and {H. Katz} and {A. Andreou}},
year = 2008,
month = {10},
booktitle = {Argentine School of Micro-Nanoelectronics, Technology and Applications},
url = {https://www.semanticscholar.org/paper/7b584f80c98f6642571120aea5583ccece453ce9},
}

Z. Zhang and A. Andreou, “Human identification experiments using acoustic micro-Doppler signatures,” in Argentine School of Micro-Nanoelectronics, Technology and Applications, 2008.
[BibTeX] [Link]

@inproceedings{14144876,
title = {Human identification experiments using acoustic micro-Doppler signatures},
author = {{Z. Zhang} and {A. Andreou}},
year = 2008,
month = {10},
booktitle = {Argentine School of Micro-Nanoelectronics, Technology and Applications},
url = {https://www.semanticscholar.org/paper/dc69d5cde5eb260c71b72ca4d794bc8664a58174},
}

A. Cassidy, Z. Zhang, and A. Andreou, “Impulse Radio Address Event Interconnects for body area networks and neural prostheses,” in Argentine School of Micro-Nanoelectronics, Technology and Applications, 2008.
[BibTeX] [Link]

@inproceedings{7784406,
title = {Impulse Radio Address Event Interconnects for body area networks and neural prostheses},
author = {{A. Cassidy} and {Z. Zhang} and {A. Andreou}},
year = 2008,
month = {10},
booktitle = {Argentine School of Micro-Nanoelectronics, Technology and Applications},
url = {https://www.semanticscholar.org/paper/a478e781f85913c349fee9718dda5c896ca3d0c4},
}

Z. Zhang and A. Andreou, “Slow moving vehicles using the microphone arrays in the Hopkins Acoustic Surveillance Unit,” in Argentine School of Micro-Nanoelectronics, Technology and Applications, 2008.
[BibTeX] [Link]

@inproceedings{18700849,
title = {Slow moving vehicles using the microphone arrays in the Hopkins Acoustic Surveillance Unit},
author = {{Z. Zhang} and {A. Andreou}},
year = 2008,
month = {10},
booktitle = {Argentine School of Micro-Nanoelectronics, Technology and Applications},
url = {https://www.semanticscholar.org/paper/cafad54a832309b7b5c5a49c6f0d7ef97d794f0a},
}

A. Andreou, “Silicon-on-sapphire CMOS and opportunities in niche markets: Old wine in a new bottle,” in 2008 IEEE International SOI Conference, 2008.
[BibTeX] [Link]

@inproceedings{34651814,
title = {Silicon-on-sapphire CMOS and opportunities in niche markets: Old wine in a new bottle},
author = {{A. Andreou}},
year = 2008,
month = {10},
booktitle = {2008 IEEE International SOI Conference},
url = {https://www.semanticscholar.org/paper/849d93b3b615e9157faab4d5f46bdb29bdbff728},
}

D. A. Smith and J. Eisner, “Dependency Parsing by Belief Propagation,” in Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Honolulu, 2008, p. 145–156.
[BibTeX] [Link]

@InProceedings{smith-eisner-2008-bp,
aclid = "D08-1016",
author = "David A. Smith and Jason Eisner",
title = "Dependency Parsing by Belief Propagation",
booktitle = "Proceedings of the Conference on Empirical Methods in
Natural Language Processing (EMNLP)",
pages = "145--156",
year = "2008",
month = oct,
address = "Honolulu",
URL = "http://cs.jhu.edu/~jason/papers/#smith-eisner-2008-bp",
}

O. F. Zaidan and J. Eisner, “Modeling Annotators: A Generative Approach to Learning from Annotator Rationales,” in Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Honolulu, 2008, p. 31–40.
[BibTeX] [Link]

@InProceedings{zaidan-eisner-2008,
aclid = "D08-1004",
author = "Omar F. Zaidan and Jason Eisner",
title = "Modeling Annotators: {A} Generative Approach to
Learning from Annotator Rationales",
booktitle = "Proceedings of the Conference on Empirical Methods in
Natural Language Processing (EMNLP)",
pages = "31--40",
year = "2008",
month = oct,
address = "Honolulu",
URL = "http://cs.jhu.edu/~jason/papers/#zaidan-eisner-2008",
}

M. Dreyer, J. R. Smith, and J. Eisner, “Latent-Variable Modeling of String Transductions with Finite-State Methods,” in Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Honolulu, 2008, p. 1080–1089.
[BibTeX] [Link]

@InProceedings{dreyer-smith-eisner-2008,
aclid = "D08-1113",
author = "Markus Dreyer and Jason R. Smith and Jason Eisner",
title = "Latent-Variable Modeling of String Transductions with
Finite-State Methods",
booktitle = "Proceedings of the Conference on Empirical Methods in
Natural Language Processing (EMNLP)",
pages = "1080--1089",
year = "2008",
month = oct,
address = "Honolulu",
URL = "http://cs.jhu.edu/~jason/papers/#dreyer-smith-eisner-2008",
}

J. Eisner and N. A. Smith, “Competitive Grammar Writing,” in Proceedings of the Third Workshop on Issues in Teaching Computational Linguistics, Columbus, Ohio, 2008, p. 97–105.
[BibTeX] [Link]

@InProceedings{eisner-smith-2008-tnlp,
aclid = "W08-0212",
author = "Jason Eisner and Noah A. Smith",
title = "Competitive Grammar Writing",
booktitle = "Proceedings of the Third Workshop on Issues in
Teaching Computational Linguistics",
pages = "97--105",
year = "2008",
month = jun,
address = "Columbus, Ohio",
URL = "http://cs.jhu.edu/~jason/papers/#eisner-smith-2008-tnlp",
}

D. Karakos, J. Eisner, Sanjeev Khudanpur, and M. Dreyer, “Machine Translation System Combination using ITG-based Alignments,” in Proceedings of ACL-08: HLT, Short Papers, Columbus, Ohio, 2008, p. 81–84.
[BibTeX] [Link]

@InProceedings{karakos-et-al-2008,
aclid = "P08-2021",
author = "Damianos Karakos and Jason Eisner and Sanjeev
Khudanpur and Markus Dreyer",
title = "Machine Translation System Combination using
{ITG}-based Alignments",
booktitle = "Proceedings of ACL-08: HLT, Short Papers",
pages = "81--84",
year = "2008",
month = jun,
address = "Columbus, Ohio",
URL = "http://cs.jhu.edu/~jason/papers/#karakos-et-al-2008",
}

M. Marwick and A. Andreou, “Photo-battery fabricated in silicon on sapphire CMOS,” in Electronics Letters, 2008.
[BibTeX] [Link]

@inproceedings{110935662,
title = {Photo-battery fabricated in silicon on sapphire CMOS},
author = {{M. Marwick} and {A. Andreou}},
year = 2008,
month = {6},
booktitle = {Electronics Letters},
url = {https://www.semanticscholar.org/paper/96233510e6db4c6f00d7c8b5cea6f9600412644f},
}

B. Pal, Jia Sun, Byung-Jun Jung, E. Choi, A. Andreou, and H. Katz, “Pentacene‐Zinc Oxide Vertical Diode with Compatible Grains and 15‐MHz Rectification,” in Advanced Materials, 2008.
[BibTeX] [Link]

@inproceedings{137931537,
title = {Pentacene‐Zinc Oxide Vertical Diode with Compatible Grains and 15‐MHz Rectification},
author = {{B. Pal} and {Jia Sun} and {Byung-Jun Jung} and {E. Choi} and {A. Andreou} and {H. Katz}},
year = 2008,
month = {3},
booktitle = {Advanced Materials},
url = {https://www.semanticscholar.org/paper/57e2a96aefbc0876cadd8807e970a95915624b2f},
}

A. Andreou, “Detection Methods of Foot Shape and Pressure Distribution.” 2008.
[BibTeX] [Link]

@inproceedings{230321552,
title = {Detection Methods of Foot Shape and Pressure Distribution},
author = {{A. Andreou}},
year = 2008,
month = {5},
booktitle = {},
url = {https://www.semanticscholar.org/paper/f0c69b728e12431a93335eb3a9b2ffac2badb6b1},
}

M. Soma, Zhi-Pei Liang, G. Yen, G. Cauwenberghs, R. Etienne-Cummings, A. Andreou, A. Bermak, A. Burdett, Toumaz Uk Ltd, S. Carrara, K. Chakrabarty, S. Chakrabartty, P. Chiang, David Cumming, T. Delbruck, T. Denison, S. DeWeerth, E. Drakakis, D. Ham, E. Jovanov, Edmund Y. L Am, Yong Lian, Shih-Chii Liu, Wentai Liu, A. J. Mason, T. Roska, R. Sarpeshkar, M. Sawan, K. Shepard, Bertram E. Shi, M. Stanaćević, and J. Spiegel, “TECHNICAL CO-SPONSORING SOCIETIES Computational Intelligence.” 2008.
[BibTeX] [Link]

@inproceedings{61657264,
title = {TECHNICAL CO-SPONSORING SOCIETIES Computational Intelligence},
author = {{M. Soma} and {Zhi-Pei Liang} and {G. Yen} and {G. Cauwenberghs} and {R. Etienne-Cummings} and {A. Andreou} and {A. Bermak} and {A. Burdett} and {Toumaz Uk Ltd} and {S. Carrara} and {K. Chakrabarty} and {S. Chakrabartty} and {P. Chiang} and {David Cumming} and {T. Delbruck} and {T. Denison} and {S. DeWeerth} and {E. Drakakis} and {D. Ham} and {E. Jovanov} and {Edmund Y. L Am} and {Yong Lian} and {Shih-Chii Liu} and {Wentai Liu} and {A. J. Mason} and {T. Roska} and {R. Sarpeshkar} and {M. Sawan} and {K. Shepard} and {Bertram E. Shi} and {M. Stanaćević} and {J. Spiegel}},
year = 2008,
booktitle = {},
url = {https://www.semanticscholar.org/paper/c266eb27639c51533c576d5ce82f6e70b6cda282},
}

M. Marwick and A. Andreou, “Single photon avalanche photodetector with integrated quenching fabricated in TSMC 0.18 μm 1.8 V CMOS process,” in Electronics Letters, 2008.
[BibTeX] [Link]

@inproceedings{111078621,
title = {Single photon avalanche photodetector with integrated quenching fabricated in TSMC 0.18 μm 1.8 V CMOS process},
author = {{M. Marwick} and {A. Andreou}},
year = 2008,
month = {5},
booktitle = {Electronics Letters},
url = {https://www.semanticscholar.org/paper/0f0d4f9bbafa7ed95df980493e7ef77739e9f7d9},
}

A. Andreou, “An Electronically Tunable Linear or Nonlinear MOS Resistor.” 2008.
[BibTeX] [Link]

@inproceedings{110307007,
title = {An Electronically Tunable Linear or Nonlinear MOS Resistor},
author = {{A. Andreou}},
year = 2008,
booktitle = {},
url = {https://www.semanticscholar.org/paper/930f882af99aef208f1eff7d7e8fc5bd2bc0139b},
}

Wei Tang, A. Andreou, and E. Culurciello, “A low-power silicon-on-sapphire tunable ultra-wideband transmitter,” in 2008 IEEE International Symposium on Circuits and Systems, 2008.
[BibTeX] [Link]

@inproceedings{28321471,
title = {A low-power silicon-on-sapphire tunable ultra-wideband transmitter},
author = {{Wei Tang} and {A. Andreou} and {E. Culurciello}},
year = 2008,
month = {5},
booktitle = {2008 IEEE International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/6b9260e6b025777c032eb81f6a5a109293ba358c},
}

M. D. Federico, P. Mandolesi, P. Julián, and A. Andreou, “Experimental results of simplicial cnn digital pixel processor,” in Electronics Letters, 2008.
[BibTeX] [Link]

@inproceedings{16856359,
title = {Experimental results of simplicial cnn digital pixel processor},
author = {{M. D. Federico} and {P. Mandolesi} and {P. Julián} and {A. Andreou}},
year = 2008,
month = {1},
booktitle = {Electronics Letters},
url = {https://www.semanticscholar.org/paper/b03ac210ef13fe095178dc5606a0c138147d888b},
}

M. Marwick and A. Andreou, “Design and characterization of a gain-enhanced floating gate-body tied photodetector in Silicon on Sapphire CMOS,” in International Semiconductor Device Research Symposium, 2007.
[BibTeX] [Link]

@inproceedings{33132178,
title = {Design and characterization of a gain-enhanced floating gate-body tied photodetector in Silicon on Sapphire CMOS},
author = {{M. Marwick} and {A. Andreou}},
year = 2007,
month = {12},
booktitle = {International Semiconductor Device Research Symposium},
url = {https://www.semanticscholar.org/paper/eb0bbb601458c8ff5ccbda23614fbce38f93ee84},
}

M. Marwick and A. Andreou, “A UV Photodetector with Internal Gain Fabricated in Silicon on Sapphire CMOS,” in Italian National Conference on Sensors, 2007.
[BibTeX] [Link]

@inproceedings{6694549,
title = {A UV Photodetector with Internal Gain Fabricated in Silicon on Sapphire CMOS},
author = {{M. Marwick} and {A. Andreou}},
year = 2007,
month = {12},
booktitle = {Italian National Conference on Sensors},
url = {https://www.semanticscholar.org/paper/95127189ab08324cb3922f0a6c592cc574301675},
}

A. Andreou, “Microsystems engineering from nano to micro and macro,” in 2007 14th IEEE International Conference on Electronics, Circuits and Systems, 2007.
[BibTeX] [Link]

@inproceedings{19696628,
title = {Microsystems engineering from nano to micro and macro},
author = {{A. Andreou}},
year = 2007,
month = {12},
booktitle = {2007 14th IEEE International Conference on Electronics, Circuits and Systems},
url = {https://www.semanticscholar.org/paper/a40c9af77cf73e410911fd3b6eeeafbbad30658e},
}

M. Marwick and A. Andreou, “A high voltage PMOS transistor for quenching of geiger-mode avalanche photodiodes in deep submicron CMOS technologies,” in International Semiconductor Device Research Symposium, 2007.
[BibTeX] [Link]

@inproceedings{39956050,
title = {A high voltage PMOS transistor for quenching of geiger-mode avalanche photodiodes in deep submicron CMOS technologies},
author = {{M. Marwick} and {A. Andreou}},
year = 2007,
month = {12},
booktitle = {International Semiconductor Device Research Symposium},
url = {https://www.semanticscholar.org/paper/0ddc680ab5e0243dc1c341910322a4141102394c},
}

A. Cassidy, S. Denham, P. Kanold, and A. Andreou, “FPGA Based Silicon Spiking Neural Array,” in 2007 IEEE Biomedical Circuits and Systems Conference, 2007.
[BibTeX] [Link]

@inproceedings{535106,
title = {FPGA Based Silicon Spiking Neural Array},
author = {{A. Cassidy} and {S. Denham} and {P. Kanold} and {A. Andreou}},
year = 2007,
month = {11},
booktitle = {2007 IEEE Biomedical Circuits and Systems Conference},
url = {https://www.semanticscholar.org/paper/cdb1d3a8fc09856480d9d838cd5fa1c7ce12aa43},
}

David H. Goldberg and A. Andreou, “Distortion of Neural Signals by Spike Coding,” in Neural Computation, 2007.
[BibTeX] [Link]

@inproceedings{17225429,
title = {Distortion of Neural Signals by Spike Coding},
author = {{David H. Goldberg} and {A. Andreou}},
year = 2007,
month = {10},
booktitle = {Neural Computation},
url = {https://www.semanticscholar.org/paper/a7262bf92982eb518d27a4f17f1922d997007e7d},
}

D. A. Smith and J. Eisner, “Bootstrapping Feature-Rich Dependency Parsers with Entropic Priors,” in Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL), Prague, 2007, p. 667–677.
[BibTeX] [Link]

@InProceedings{smith-eisner-2007,
aclid = "D07-1070",
author = "David A. Smith and Jason Eisner",
title = "Bootstrapping Feature-Rich Dependency Parsers with
Entropic Priors",
booktitle = "Proceedings of the 2007 Joint Conference on Empirical
Methods in Natural Language Processing and
Computational Natural Language Learning (EMNLP-CoNLL)",
pages = "667--677",
year = "2007",
month = jun,
address = "Prague",
URL = "http://cs.jhu.edu/~jason/papers/#smith-eisner-2007",
}

O. Zaidan, J. Eisner, and C. Piatko, “Using “Annotator Rationales” to Improve Machine Learning for Text Categorization,” in Human Language Technologies: Proceedings of the Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT), Rochester, NY, 2007, p. 260–267.
[BibTeX] [Link]

@InProceedings{zaidan-eisner-piatko-2007,
aclid = "N07-1033",
author = "Omar Zaidan and Jason Eisner and Christine Piatko",
title = "Using ``Annotator Rationales'' to Improve Machine
Learning for Text Categorization",
booktitle = "Human Language Technologies: Proceedings of the Annual
Conference of the North American Chapter of the
Association for Computational Linguistics (NAACL-HLT)",
pages = "260--267",
year = "2007",
month = apr,
address = "Rochester, NY",
URL = "http://cs.jhu.edu/~jason/papers/#zaidan-eisner-piatko-2007",
}

D. Karakos, J. Eisner, Sanjeev Khudanpur, and C. E. Priebe, “Cross-Instance Tuning of Unsupervised Document Clustering Algorithms,” in Human Language Technologies: Proceedings of the Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT), Rochester, NY, 2007, p. 252–259.
[BibTeX] [Link]

@InProceedings{karakos-et-al-2007-naacl,
aclid = "N07-1032",
author = "Damianos Karakos and Jason Eisner and Sanjeev
Khudanpur and Carey E. Priebe",
title = "Cross-Instance Tuning of Unsupervised Document
Clustering Algorithms",
booktitle = "Human Language Technologies: Proceedings of the Annual
Conference of the North American Chapter of the
Association for Computational Linguistics (NAACL-HLT)",
year = "2007",
month = apr,
address = "Rochester, NY",
pages = "252--259",
URL = "http://cs.jhu.edu/~jason/papers/#karakos-et-al-2007-naacl",
}

D. Karakos, S. Khudanpur, Jason Eisner, and C. E. Priebe, “Iterative Denoising Using Jensen-Renyí Divergences with an Application to Unsupervised Document Categorization,” in Proceedings of the International Conference on Acoustics, Speech and Signal Processing (ICASSP), Honolulu, 2007.
[BibTeX] [Link]

@InProceedings{karakos-et-al-2007-icassp,
author = "Damianos Karakos and Sanjeev Khudanpur and Jason
Eisner and Carey E. Priebe",
title = "Iterative Denoising Using {J}ensen-{R}eny\'{\i}
Divergences with an Application to Unsupervised
Document Categorization",
booktitle = "Proceedings of the International Conference on
Acoustics, Speech and Signal Processing (ICASSP)",
note = "4 pages",
year = "2007",
month = apr,
address = "Honolulu",
URL = "http://cs.jhu.edu/~jason/papers/#karakos-et-al-2007-icassp",
}

J. Christen and A. Andreou, “A Self-Biased Operational Transconductance Amplifier in 0.18 micron 3D SOI-CMOS,” in 2007 IEEE International Symposium on Circuits and Systems, 2007.
[BibTeX] [Link]

@inproceedings{20142766,
title = {A Self-Biased Operational Transconductance Amplifier in 0.18 micron 3D SOI-CMOS},
author = {{J. Christen} and {A. Andreou}},
year = 2007,
month = {5},
booktitle = {2007 IEEE International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/07af8f2c812e1799671ccfba911a513819c6d52e},
}

Z. Zhang, P. Pouliquen, A. Waxman, and A. Andreou, “Acoustic micro-Doppler radar for human gait imaging.,” in Journal of the Acoustical Society of America, 2007.
[BibTeX] [Link]

@inproceedings{43367566,
title = {Acoustic micro-Doppler radar for human gait imaging.},
author = {{Z. Zhang} and {P. Pouliquen} and {A. Waxman} and {A. Andreou}},
year = 2007,
month = {2},
booktitle = {Journal of the Acoustical Society of America},
url = {https://www.semanticscholar.org/paper/cf3b1b15293afd79a6feac97a89b1b6e1d1d69db},
}

A. Andreou, Jie Chen, P. Chung, and Stephen T. C. Wong, “Enabling Technologies in Drug Delivery and Clinical Care,” in 2007 IEEE International Symposium on Circuits and Systems, 2007.
[BibTeX] [Link]

@inproceedings{11927906,
title = {Enabling Technologies in Drug Delivery and Clinical Care},
author = {{A. Andreou} and {Jie Chen} and {P. Chung} and {Stephen T. C. Wong}},
year = 2007,
month = {5},
booktitle = {2007 IEEE International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/edc84a68dc38bee9d9363dedebe6d78df26a3e2f},
}

J. Georgiou and A. Andreou, “Address-data event representation for communication in multichip neuromorphic system architectures,” in Electronics Letters, 2007.
[BibTeX] [Link]

@inproceedings{58464138,
title = {Address-data event representation for communication in multichip neuromorphic system architectures},
author = {{J. Georgiou} and {A. Andreou}},
year = 2007,
month = {7},
booktitle = {Electronics Letters},
url = {https://www.semanticscholar.org/paper/15e555ff7a0483466bcb3870fb85b37190bc7003},
}

J. Christen and A. Andreou, “Design, Fabrication, and Testing of a Hybrid CMOS/PDMS Microsystem for Cell Culture and Incubation,” in IEEE Transactions on Biomedical Circuits and Systems, 2007.
[BibTeX] [Link]

@inproceedings{1252647,
title = {Design, Fabrication, and Testing of a Hybrid CMOS/PDMS Microsystem for Cell Culture and Incubation},
author = {{J. Christen} and {A. Andreou}},
year = 2007,
month = {7},
booktitle = {IEEE Transactions on Biomedical Circuits and Systems},
url = {https://www.semanticscholar.org/paper/fffa9180c2f2749a171b25a50a0ad65820744de4},
}

M. Marwick and A. Andreou, “Fabrication and Testing of Single Photon Avalanche Detectors in the TSMC 0.18μm CMOS Technology,” in Annual Conference on Information Sciences and Systems, 2007.
[BibTeX] [Link]

@inproceedings{17087252,
title = {Fabrication and Testing of Single Photon Avalanche Detectors in the TSMC 0.18μm CMOS Technology},
author = {{M. Marwick} and {A. Andreou}},
year = 2007,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/0a1d9d8ff27e1aa8371bba67cee89a44687ab285},
}

E. Choi and A. Andreou, “Architecture of a μRFID with integrated antenna in 3D SOI-CMOS,” in Annual Conference on Information Sciences and Systems, 2007.
[BibTeX] [Link]

@inproceedings{16685473,
title = {Architecture of a μRFID with integrated antenna in 3D SOI-CMOS},
author = {{E. Choi} and {A. Andreou}},
year = 2007,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/41eb662a44bdc1e2e66fd745fded8bf13b298f1d},
}

E. Culurciello, P. Pouliquen, and A. Andreou, “Digital isolation amplifier in silicon-on-sapphire CMOS,” in Electronics Letters, 2007.
[BibTeX] [Link]

@inproceedings{110077446,
title = {Digital isolation amplifier in silicon-on-sapphire CMOS},
author = {{E. Culurciello} and {P. Pouliquen} and {A. Andreou}},
year = 2007,
month = {4},
booktitle = {Electronics Letters},
url = {https://www.semanticscholar.org/paper/e8bbf1f1f93eb96bcc618ef64e2e855502cb017b},
}

Z. Zhang, P. Pouliquen, A. Waxman, and A. Andreou, “Acoustic Micro-Doppler Gait Signatures of Humans and Animals,” in Annual Conference on Information Sciences and Systems, 2007.
[BibTeX] [Link]

@inproceedings{396554,
title = {Acoustic Micro-Doppler Gait Signatures of Humans and Animals},
author = {{Z. Zhang} and {P. Pouliquen} and {A. Waxman} and {A. Andreou}},
year = 2007,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/a5e97fb77acfad82403eff3d6bd758288f22066e},
}

A. Andreou and J. Christen, “Hybrid integration of silicon/silicone microsystems: a closed-loop, autonomous micro-incubator.” 2007.
[BibTeX] [Link]

@inproceedings{114165149,
title = {Hybrid integration of silicon/silicone microsystems: a closed-loop, autonomous micro-incubator},
author = {{A. Andreou} and {J. Christen}},
year = 2007,
booktitle = {},
url = {https://www.semanticscholar.org/paper/9475e7c5a385c89e6c95ef670eb82ef53b33a625},
}

Z. Zhang and A. Andreou, “Design of An Ultra Wideband Transmitter in 0.18μm 3D Silicon on Insulator CMOS,” in Annual Conference on Information Sciences and Systems, 2007.
[BibTeX] [Link]

@inproceedings{17540825,
title = {Design of An Ultra Wideband Transmitter in 0.18μm 3D Silicon on Insulator CMOS},
author = {{Z. Zhang} and {A. Andreou}},
year = 2007,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/c93033a2484406a5cad6bce5b4fc45bae2714867},
}

J. Christen, A. Andreou, and B. Iglehart, “Localized closed-loop temperature control and regulation in hybrid silicon/silicone life science microsystems,” in 2007 IEEE International Symposium on Circuits and Systems, 2007.
[BibTeX] [Link]

@inproceedings{23535312,
title = {Localized closed-loop temperature control and regulation in hybrid silicon/silicone life science microsystems},
author = {{J. Christen} and {A. Andreou} and {B. Iglehart}},
year = 2007,
month = {5},
booktitle = {2007 IEEE International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/7077438a107986aeedffd3bb5a5f01904a5e089f},
}

J. Christen and A. Andreou, “Design, Analysis and Implementation of Integrated Micro-Thermal Control Systems,” in 2007 IEEE International Symposium on Circuits and Systems, 2007.
[BibTeX] [Link]

@inproceedings{2075156,
title = {Design, Analysis and Implementation of Integrated Micro-Thermal Control Systems},
author = {{J. Christen} and {A. Andreou}},
year = 2007,
month = {5},
booktitle = {2007 IEEE International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/659b86a5822e3bb09e839d70871f302c7908b81e},
}

J. Georgiou and A. Andreou, “Address Data Event Representation (ADER) for Efficient Neuromorphic Communication,” in Annual Conference on Information Sciences and Systems, 2007.
[BibTeX] [Link]

@inproceedings{774299,
title = {Address Data Event Representation (ADER) for Efficient Neuromorphic Communication},
author = {{J. Georgiou} and {A. Andreou}},
year = 2007,
month = {3},
booktitle = {Annual Conference on Information Sciences and Systems},
url = {https://www.semanticscholar.org/paper/9f277ef9ea827d95dfd3ee52910f8130bb240638},
}

J. Eisner and J. Blatz, “Program Transformations for Optimization of Parsing Algorithms and Other Weighted Logic Programs,” in Proceedings of FG 2006: The 11th Conference on Formal Grammar, 2007, p. 45–85.
[BibTeX] [Link]

@InProceedings{eisner-blatz-2007,
author = "Jason Eisner and John Blatz",
title = "Program Transformations for Optimization of Parsing
Algorithms and Other Weighted Logic Programs",
booktitle = "Proceedings of FG 2006: The 11th Conference on Formal
Grammar",
pages = "45--85",
year = "2007",
editor = "Shuly Wintner",
publisher = "CSLI Publications",
URL = "http://cs.jhu.edu/~jason/papers/#eisner-blatz-2007",
}

E. Culurciello and A. Andreou, “Capacitive Inter-Chip Data and Power Transfer for 3-D VLSI,” in IEEE Transactions on Circuits and Systems – II – Express Briefs, 2006.
[BibTeX] [Link]

@inproceedings{28828770,
title = {Capacitive Inter-Chip Data and Power Transfer for 3-D VLSI},
author = {{E. Culurciello} and {A. Andreou}},
year = 2006,
month = {12},
booktitle = {IEEE Transactions on Circuits and Systems - II - Express Briefs},
url = {https://www.semanticscholar.org/paper/bf171d71b22d5cf219ad410fd2a9c06c55c3bbb8},
}

J. Christen and A. Andreou, “Hybrid integration for autonomous, closed-loop cell culture and incubation,” in Nanomedicine: Nanotechnology, Biology and Medicine, 2006.
[BibTeX] [Link]

@inproceedings{135774967,
title = {Hybrid integration for autonomous, closed-loop cell culture and incubation},
author = {{J. Christen} and {A. Andreou}},
year = 2006,
month = {12},
booktitle = {Nanomedicine: Nanotechnology, Biology and Medicine},
url = {https://www.semanticscholar.org/paper/e40043919c5a4ec0fb0c201f0eb1ade9e0183866},
}

J.M. Blain Christen and A. Andreou, “Integrated PDMS/CMOS Microsystem for Autonomous Incubation and Imaging in Cell Culture Studies,” in 2006 IEEE/NLM Life Science Systems and Applications Workshop, 2006.
[BibTeX] [Link]

@inproceedings{17549385,
title = {Integrated PDMS/CMOS Microsystem for Autonomous Incubation and Imaging in Cell Culture Studies},
author = {{J.M. Blain Christen} and {A. Andreou}},
year = 2006,
month = {11},
booktitle = {2006 IEEE/NLM Life Science Systems and Applications Workshop},
url = {https://www.semanticscholar.org/paper/05cdbf3c044bc1bae5f318e24c4d97f1588819bb},
}

A. Andreou, P. Chung, Guang‐Zhong Yang, and S. Wong, “Special issue on advances in life science systems and applications: Guest editorial.” 2006.
[BibTeX] [Link]

@inproceedings{16677717,
title = {Special issue on advances in life science systems and applications: Guest editorial},
author = {{A. Andreou} and {P. Chung} and {Guang‐Zhong Yang} and {S. Wong}},
year = 2006,
month = {11},
booktitle = {},
url = {https://www.semanticscholar.org/paper/97f8eb3bdda51a7285c049eb3a79d90da3a56f52},
}

David H. Goldberg, A. Andreou, P. Julián, P. Pouliquen, Laurence Riddle, and Rich Rosasco, “VLSI implementation of an energy-aware wake-up detector for an acoustic surveillance sensor network,” in TOSN, 2006.
[BibTeX] [Link]

@inproceedings{6736227,
title = {VLSI implementation of an energy-aware wake-up detector for an acoustic surveillance sensor network},
author = {{David H. Goldberg} and {A. Andreou} and {P. Julián} and {P. Pouliquen} and {Laurence Riddle} and {Rich Rosasco}},
year = 2006,
month = {11},
booktitle = {TOSN},
url = {https://www.semanticscholar.org/paper/e3bb4400e6eedfedc9f37f687a86039bca8757cd},
}

P. Julián, F. N. M. Pirchio, and A. Andreou, “Experimental results for cascadable micropower time delay estimator,” in Electronics Letters, 2006.
[BibTeX] [Link]

@inproceedings{111002903,
title = {Experimental results for cascadable micropower time delay estimator},
author = {{P. Julián} and {F. N. M. Pirchio} and {A. Andreou}},
year = 2006,
month = {10},
booktitle = {Electronics Letters},
url = {https://www.semanticscholar.org/paper/dbb64ee184793bacc681318b35892e1fd5439e6c},
}

E. Culurciello and A. Andreou, “CMOS image sensors for sensor networks,” in Analog Integrated Circuits and Signal Processing, 2006.
[BibTeX] [Link]

@inproceedings{41929501,
title = {CMOS image sensors for sensor networks},
author = {{E. Culurciello} and {A. Andreou}},
year = 2006,
month = {10},
booktitle = {Analog Integrated Circuits and Signal Processing},
url = {https://www.semanticscholar.org/paper/5560fd5e58c25ce864738cf764341305ba758f90},
}

G. Marcus, Kim Strohben, S. Jaskulek, A. Andreou, and E. Culurciello, “A monolithic isolation amplifier in silicon-on-insulator CMOS: Testing and applications,” in Analog Integrated Circuits and Signal Processing, 2006.
[BibTeX] [Link]

@inproceedings{62187386,
title = {A monolithic isolation amplifier in silicon-on-insulator CMOS: Testing and applications},
author = {{G. Marcus} and {Kim Strohben} and {S. Jaskulek} and {A. Andreou} and {E. Culurciello}},
year = 2006,
month = {10},
booktitle = {Analog Integrated Circuits and Signal Processing},
url = {https://www.semanticscholar.org/paper/0baff22901722ea21b0614228f2bee905d25d91c},
}

J. Eisner, M. Kornbluh, G. Woodhull, R. Buse, S. Huang, Constantinos Michael, and G. Shafer, “Visual Navigation Through Large Directed Graphs and Hypergraphs,” in Proceedings of the IEEE Symposium on Information Visualization (InfoVis’06), Poster/Demo Session, Baltimore, 2006, p. 116–117.
[BibTeX] [Link]

@InProceedings{DYNASTY-2006,
author = "Jason Eisner and Michael Kornbluh and Gordon Woodhull
and Raymond Buse and Samuel Huang and Constantinos
Michael and George Shafer",
title = "Visual Navigation Through Large Directed Graphs and
Hypergraphs",
booktitle = "Proceedings of the IEEE Symposium on Information
Visualization (InfoVis'06), Poster/Demo Session",
pages = "116--117",
year = "2006",
month = oct,
address = "Baltimore",
URL = "http://cs.jhu.edu/~jason/papers/#DYNASTY-2006",
}

J. Mason, K. Watkins, J. Eisner, and A. Stubblefield, “A Natural-Language Approach to Automated Cryptanalysis of Two-Time Pads,” in Proceedings of the ACM Conference on Computer and Communications Security (ACM CCS), Alexandria, VA, 2006, p. 235–244.
[BibTeX] [Link]

@InProceedings{mason-et-al-2006,
author = "Joshua Mason and Kathryn Watkins and Jason Eisner and
Adam Stubblefield",
title = "A Natural-Language Approach to Automated Cryptanalysis
of Two-Time Pads",
booktitle = "Proceedings of the ACM Conference on Computer and
Communications Security (ACM CCS)",
pages = "235--244",
year = "2006",
month = oct,
address = "Alexandria, VA",
URL = "http://cs.jhu.edu/~jason/papers/#mason-et-al-2006",
}

M. Dreyer and J. Eisner, “Better Informed Training of Latent Syntactic Features,” in Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Sydney, 2006, p. 317–326.
[BibTeX] [Link]

@InProceedings{dreyer-eisner-2006,
aclid = "W06-1638",
author = "Markus Dreyer and Jason Eisner",
title = "Better Informed Training of Latent Syntactic
Features",
booktitle = "Proceedings of the Conference on Empirical Methods in
Natural Language Processing (EMNLP)",
pages = "317--326",
year = "2006",
month = jul,
address = "Sydney",
URL = "http://cs.jhu.edu/~jason/papers/#dreyer-eisner-2006",
}

D. A. Smith and J. Eisner, “Minimum-Risk Annealing for Training Log-Linear Models,” in Proceedings of the International Conference on Computational Linguistics and the Association for Computational Linguistics (COLING-ACL), Companion Volume, Sydney, 2006, p. 787–794.
[BibTeX] [Link]

@InProceedings{smith-eisner-2006-acl-risk,
aclid = "P06-2101",
author = "David A. Smith and Jason Eisner",
title = "Minimum-Risk Annealing for Training Log-Linear
Models",
booktitle = "Proceedings of the International Conference on
Computational Linguistics and the Association for
Computational Linguistics (COLING-ACL), Companion
Volume",
pages = "787--794",
year = "2006",
month = jul,
address = "Sydney",
URL = "http://cs.jhu.edu/~jason/papers/#smith-eisner-2006-acl-risk",
}

N. A. Smith and J. Eisner, “Annealing Structural Bias in Multilingual Weighted Grammar Induction,” in Proceedings of the International Conference on Computational Linguistics and the Association for Computational Linguistics (COLING-ACL), Sydney, 2006, p. 569–576.
[BibTeX] [Link]

@InProceedings{smith-eisner-2006-acl-sa,
aclid = "P06-1072",
author = "Noah A. Smith and Jason Eisner",
title = "Annealing Structural Bias in Multilingual Weighted
Grammar Induction",
booktitle = "Proceedings of the International Conference on
Computational Linguistics and the Association for
Computational Linguistics (COLING-ACL)",
pages = "569--576",
year = "2006",
month = jul,
address = "Sydney",
URL = "http://cs.jhu.edu/~jason/papers/#smith-eisner-2006-acl-sa",
}

J. Eisner and R. W. Tromble, “Local Search with Very Large-Scale Neighborhoods for Optimal Permutations in Machine Translation,” in Proceedings of the HLT-NAACL Workshop on Computationally Hard Problems and Joint Inference in Speech and Language Processing, New York, 2006, p. 57–75.
[BibTeX] [Link]

@InProceedings{eisner-tromble-2006,
author = "Jason Eisner and Roy W. Tromble",
title = "Local Search with Very Large-Scale Neighborhoods for
Optimal Permutations in Machine Translation",
booktitle = "Proceedings of the HLT-NAACL Workshop on
Computationally Hard Problems and Joint Inference in
Speech and Language Processing",
pages = "57--75",
year = "2006",
month = jun,
address = "New York",
URL = "http://cs.jhu.edu/~jason/papers/#eisner-tromble-2006",
}

D. A. Smith and J. Eisner, “Quasi-Synchronous Grammars: Alignment by Soft Projection of Syntactic Dependencies,” in Proceedings of the HLT-NAACL Workshop on Statistical Machine Translation, New York, 2006, p. 23–30.
[BibTeX] [Link]

@InProceedings{smith-eisner-2006-smt,
aclid = "W06-3104",
author = "David A. Smith and Jason Eisner",
title = "Quasi-Synchronous Grammars: Alignment by Soft
Projection of Syntactic Dependencies",
booktitle = "Proceedings of the HLT-NAACL Workshop on Statistical
Machine Translation",
pages = "23--30",
year = "2006",
month = jun,
address = "New York",
note = "Nominated for 5-year retrospective Best Paper award.",
URL = "http://cs.jhu.edu/~jason/papers/#smith-eisner-2006-smt",
}

R. W. Tromble and J. Eisner, “A Fast Finite-State Relaxation Method for Enforcing Global Constraints on Sequence Decoding,” in Proceedings of the Human Language Technology Conference of the North American Association for Computational Linguistics (HLT-NAACL), New York, 2006, p. 423–430.
[BibTeX] [Link]

@InProceedings{tromble-eisner-2006,
aclid = "N06-1054",
author = "Roy W. Tromble and Jason Eisner",
title = "A Fast Finite-State Relaxation Method for Enforcing
Global Constraints on Sequence Decoding",
booktitle = "Proceedings of the Human Language Technology
Conference of the North American Association for
Computational Linguistics (HLT-NAACL)",
pages = "423--430",
year = "2006",
month = jun,
address = "New York",
URL = "http://cs.jhu.edu/~jason/papers/#tromble-eisner-2006",
}

E. Culurciello and A. Andreou, “An 8-bit 800-$muhboxW$1.23-MS/s Successive Approximation ADC in SOI CMOS,” in IEEE Transactions on Circuits and Systems – II – Express Briefs, 2006.
[BibTeX] [Link]

@inproceedings{25906118,
title = {An 8-bit 800-$muhboxW$1.23-MS/s Successive Approximation ADC in SOI CMOS},
author = {{E. Culurciello} and {A. Andreou}},
year = 2006,
month = {9},
booktitle = {IEEE Transactions on Circuits and Systems - II - Express Briefs},
url = {https://www.semanticscholar.org/paper/869169a56616c156fb4b2775e2d3fd885870b1ef},
}

P. Julián, A. Andreou, and David H. Goldberg, “A low-power correlation-derivative CMOS VLSI circuit for bearing estimation,” in IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2006.
[BibTeX] [Link]

@inproceedings{6053956,
title = {A low-power correlation-derivative CMOS VLSI circuit for bearing estimation},
author = {{P. Julián} and {A. Andreou} and {David H. Goldberg}},
year = 2006,
month = {2},
booktitle = {IEEE Transactions on Very Large Scale Integration (VLSI) Systems},
url = {https://www.semanticscholar.org/paper/8659e1260299d11e89c80f2201f16faee1b86c9d},
}

Thiago Teixeira, E. Culurciello, and A. Andreou, “An Address-Event Image Sensor Network,” in 2006 IEEE International Symposium on Circuits and Systems, 2006.
[BibTeX] [Link]

@inproceedings{6132660,
title = {An Address-Event Image Sensor Network},
author = {{Thiago Teixeira} and {E. Culurciello} and {A. Andreou}},
year = 2006,
month = {5},
booktitle = {2006 IEEE International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/e2d47210a12160afecf78eb30ca3275b696cf9f6},
}

M. Marwick and A. Andreou, “Retinomorphic system design in three dimensional SOI-CMOS,” in 2006 IEEE International Symposium on Circuits and Systems, 2006.
[BibTeX] [Link]

@inproceedings{8853781,
title = {Retinomorphic system design in three dimensional SOI-CMOS},
author = {{M. Marwick} and {A. Andreou}},
year = 2006,
month = {5},
booktitle = {2006 IEEE International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/962aa0ce67f8b64061c7878a9073025f118148ff},
}

M. Marwick, Francisco Tejada, P. Pouliquen, E. Culurciello, K. Strohbehn, and A. Andreou, “Dark current and noise of 100nm thick silicon on sapphire CMOS lateral PIN photodiodes,” in 2006 IEEE International Symposium on Circuits and Systems, 2006.
[BibTeX] [Link]

@inproceedings{22413744,
title = {Dark current and noise of 100nm thick silicon on sapphire CMOS lateral PIN photodiodes},
author = {{M. Marwick} and {Francisco Tejada} and {P. Pouliquen} and {E. Culurciello} and {K. Strohbehn} and {A. Andreou}},
year = 2006,
month = {5},
booktitle = {2006 IEEE International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/728e8535977fe37f6754dd73f60dfbe7e1603d78},
}

P. Mandolesi, P. Julián, and A. Andreou, “A simplicial CNN visual processor in 3D SOI-CMOS,” in 2006 IEEE International Symposium on Circuits and Systems, 2006.
[BibTeX] [Link]

@inproceedings{15013898,
title = {A simplicial CNN visual processor in 3D SOI-CMOS},
author = {{P. Mandolesi} and {P. Julián} and {A. Andreou}},
year = 2006,
month = {5},
booktitle = {2006 IEEE International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/01144a80c37c7b79ed7841748479cd6bc8db5d9b},
}

Jennifer M. BlainChristen and A. Andreou, “Integrated PDMS/CMOSMicrosystem forAutonomous Incubation and Imaging inCellCulture Studies.” 2006.
[BibTeX] [Link]

@inproceedings{138266011,
title = {Integrated PDMS/CMOSMicrosystem forAutonomous Incubation and Imaging inCellCulture Studies},
author = {{Jennifer M. BlainChristen} and {A. Andreou}},
year = 2006,
booktitle = {},
url = {https://www.semanticscholar.org/paper/9defd0f90c96bd00b0bbc1f37967df3c40a71fce},
}

Francisco Tejada, A. Andreou, and P. Pouliquen, “Stacked, standing wave detectors in 3D SOI-CMOS,” in 2006 IEEE International Symposium on Circuits and Systems, 2006.
[BibTeX] [Link]

@inproceedings{23193472,
title = {Stacked, standing wave detectors in 3D SOI-CMOS},
author = {{Francisco Tejada} and {A. Andreou} and {P. Pouliquen}},
year = 2006,
month = {5},
booktitle = {2006 IEEE International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/630a6ed484c28f2329523712460ff398f249d112},
}

J. Christen and A. Andreou, “Hybrid Silicon/Silicone (polydimethylsiloxane) Microsystem for Cell Culture,” in Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2006.
[BibTeX] [Link]

@inproceedings{47118668,
title = {Hybrid Silicon/Silicone (polydimethylsiloxane) Microsystem for Cell Culture},
author = {{J. Christen} and {A. Andreou}},
year = 2006,
booktitle = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society},
url = {https://www.semanticscholar.org/paper/1493f1a2d1a18286aa6a2c170ee1076b2b4cb665},
}

E. Culurciello, P. Pouliquen, and A. Andreou, “Digital phase-shift modulation for an isolation buffer in silicon-on-sapphire CMOS,” in 2006 IEEE International Symposium on Circuits and Systems, 2006.
[BibTeX] [Link]

@inproceedings{16707225,
title = {Digital phase-shift modulation for an isolation buffer in silicon-on-sapphire CMOS},
author = {{E. Culurciello} and {P. Pouliquen} and {A. Andreou}},
year = 2006,
month = {5},
booktitle = {2006 IEEE International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/714a9c9fadc59ebd150222f0ad9c4067c436b031},
}

J. Georgiou and A. Andreou, “High-speed, address-encoding arbiter architecture,” in Electronics Letters, 2006.
[BibTeX] [Link]

@inproceedings{62152556,
title = {High-speed, address-encoding arbiter architecture},
author = {{J. Georgiou} and {A. Andreou}},
year = 2006,
month = {2},
booktitle = {Electronics Letters},
url = {https://www.semanticscholar.org/paper/bbab19fec5a003aa7223c7ef629824427bc77db8},
}

J. Georgiou, A. Andreou, and P. Pouliquen, “A mixed analog/digital asynchronous processor for cortical computations in 3D SOI-CMOS,” in 2006 IEEE International Symposium on Circuits and Systems, 2006.
[BibTeX] [Link]

@inproceedings{18402065,
title = {A mixed analog/digital asynchronous processor for cortical computations in 3D SOI-CMOS},
author = {{J. Georgiou} and {A. Andreou} and {P. Pouliquen}},
year = 2006,
month = {5},
booktitle = {2006 IEEE International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/47083729fba1bc4296ce60fc8e3fb9faf418fe02},
}

E. Culurciello and A. Andreou, “3D integrated sensors in silicon-on-sapphire CMOS,” in 2006 IEEE International Symposium on Circuits and Systems, 2006.
[BibTeX] [Link]

@inproceedings{2705729,
title = {3D integrated sensors in silicon-on-sapphire CMOS},
author = {{E. Culurciello} and {A. Andreou}},
year = 2006,
month = {5},
booktitle = {2006 IEEE International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/03fdd243a89c134ffd51cabca98be2fd359aa17e},
}

E. Choi, Yingkai Liu, E. Smela, and A. Andreou, “System for deposition and characterization of polypyrrole/gold bilayer hinges,” in 2006 IEEE International Symposium on Circuits and Systems, 2006.
[BibTeX] [Link]

@inproceedings{2861907,
title = {System for deposition and characterization of polypyrrole/gold bilayer hinges},
author = {{E. Choi} and {Yingkai Liu} and {E. Smela} and {A. Andreou}},
year = 2006,
month = {5},
booktitle = {2006 IEEE International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/2a188b09f820905a1cdc2fc973a476df9e13cea7},
}

E. Choi, Zhiyong Gu, D. Gracias, and A. Andreou, “Chip-scale magnetic sensing and control of nanoparticles and nanorods,” in 2006 IEEE International Symposium on Circuits and Systems, 2006.
[BibTeX] [Link]

@inproceedings{11496371,
title = {Chip-scale magnetic sensing and control of nanoparticles and nanorods},
author = {{E. Choi} and {Zhiyong Gu} and {D. Gracias} and {A. Andreou}},
year = 2006,
month = {5},
booktitle = {2006 IEEE International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/a97df2f3acf9689b414abf170266a7f45773819b},
}

Francisco Tejada and A. Andreou, “Microelectromechanical systems in 3D SOI-CMOS: sensing electronics embedded in mechanical structures,” in 2006 IEEE International Symposium on Circuits and Systems, 2006.
[BibTeX] [Link]

@inproceedings{18057741,
title = {Microelectromechanical systems in 3D SOI-CMOS: sensing electronics embedded in mechanical structures},
author = {{Francisco Tejada} and {A. Andreou}},
year = 2006,
month = {5},
booktitle = {2006 IEEE International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/ef40a56e2434aa0d9db45241354ce14d6d95c7b7},
}

J. Christen and A. Andreou, “Hybrid silicon/silicone (polydimethylsiloxane) microsystem for cell culture,” in 2006 IEEE International Symposium on Circuits and Systems, 2006.
[BibTeX] [Link]

@inproceedings{1094509,
title = {Hybrid silicon/silicone (polydimethylsiloxane) microsystem for cell culture},
author = {{J. Christen} and {A. Andreou}},
year = 2006,
month = {5},
booktitle = {2006 IEEE International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/2d5278f4e9b8ae905379c5008e4282ae4420919c},
}

J. Eisner and N. A. Smith, “Parsing with Soft and Hard Constraints on Dependency Length,” in Proceedings of the International Workshop on Parsing Technologies (IWPT), Vancouver, 2005, p. 30–41.
[BibTeX] [Link]

@InProceedings{eisner-smith-2005,
aclid = "W05-1504",
author = "Jason Eisner and Noah A. Smith",
title = "Parsing with Soft and Hard Constraints on Dependency
Length",
booktitle = "Proceedings of the International Workshop on Parsing
Technologies (IWPT)",
pages = "30--41",
year = "2005",
month = oct,
address = "Vancouver",
URL = "http://cs.jhu.edu/~jason/papers/#eisner-smith-2005",
}

J. Eisner and D. Karakos, “Bootstrapping Without the Boot,” in Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing (HLT-EMNLP), Vancouver, 2005, p. 395–402.
[BibTeX] [Link]

@InProceedings{eisner-karakos-2005,
aclid = "H05-1050",
author = "Jason Eisner and Damianos Karakos",
title = "Bootstrapping Without the Boot",
booktitle = "Proceedings of Human Language Technology Conference
and Conference on Empirical Methods in Natural Language
Processing (HLT-EMNLP)",
pages = "395--402",
year = "2005",
month = oct,
address = "Vancouver",
URL = "http://cs.jhu.edu/~jason/papers/#eisner-karakos-2005",
}

J. Eisner, E. Goldlust, and N. A. Smith, “Compiling Comp Ling: Weighted Dynamic Programming and the Dyna Language,” in Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing (HLT-EMNLP), Vancouver, 2005, p. 281–290.
[BibTeX] [Link]

@InProceedings{eisner-goldlust-smith-2005,
aclid = "H05-1036",
author = "Jason Eisner and Eric Goldlust and Noah A. Smith",
title = "Compiling Comp Ling: Weighted Dynamic Programming and
the {D}yna Language",
booktitle = "Proceedings of Human Language Technology Conference
and Conference on Empirical Methods in Natural Language
Processing (HLT-EMNLP)",
pages = "281--290",
year = "2005",
month = oct,
address = "Vancouver",
URL = "http://cs.jhu.edu/~jason/papers/#eisner-goldlust-smith-2005",
}

N. A. Smith and J. Eisner, “Guiding Unsupervised Grammar Induction Using Contrastive Estimation,” in International Joint Conference on Artificial Intelligence (IJCAI) Workshop on Grammatical Inference Applications, Edinburgh, 2005, p. 73–82.
[BibTeX] [Link]

@InProceedings{smith-eisner-2005-gia,
author = "Noah A. Smith and Jason Eisner",
title = "Guiding Unsupervised Grammar Induction Using
Contrastive Estimation",
booktitle = "International Joint Conference on Artificial
Intelligence (IJCAI) Workshop on Grammatical Inference
Applications",
pages = "73--82",
year = "2005",
month = jul,
address = "Edinburgh",
URL = "http://cs.jhu.edu/~jason/papers/#smith-eisner-2005-gia",
}

N. A. Smith and J. Eisner, “Contrastive Estimation: Training Log-Linear Models on Unlabeled Data,” in Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL), Ann Arbor, Michigan, 2005, p. 354–362.
[BibTeX] [Link]

@InProceedings{smith-eisner-2005-acl,
aclid = "P05-1044",
author = "Noah A. Smith and Jason Eisner",
title = "Contrastive Estimation: Training Log-Linear Models on
Unlabeled Data",
booktitle = "Proceedings of the 43rd Annual Meeting of the
Association for Computational Linguistics (ACL)",
pages = "354--362",
year = "2005",
month = jun,
address = "Ann Arbor, Michigan",
note = "Nominated for Best Paper Award.",
URL = "http://cs.jhu.edu/~jason/papers/#smith-eisner-2005-acl",
}

A. Kempe, J. Champarnaud, Jason Eisner, F. Guingne, and F. Nicart, “A Class of Rational $n$-WFSM Auto-Intersections,” in Proceedings of the Tenth International Conference on Implementation and Application of Automata (CIAA-2005), Sophia Antipolis, France, 2005, p. 189–200.
[BibTeX] [Link]

@InProceedings{kempe-et-al-2005,
author = "Andr\'{e} Kempe and Jean-Marc Champarnaud and Jason
Eisner and Franck Guingne and Florent Nicart",
title = "A Class of Rational {$n$-WFSM} Auto-Intersections",
booktitle = "Proceedings of the Tenth International Conference on
Implementation and Application of Automata
(CIAA-2005)",
pages = "189--200",
series = "Lecture Notes in Computer Science",
number = "3845",
publisher = "Springer-Verlag",
year = "2005",
month = jun,
address = "Sophia Antipolis, France",
URL = "http://cs.jhu.edu/~jason/papers/#kempe-et-al-2005",
}

D. Karakos, S. Khudanpur, Jason Eisner, and C. E. Priebe, “Unsupervised Classification via Decision Trees: An Information-Theoretic Perspective,” in Proceedings of the 2005 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Philadelphia, 2005, p. 1081–1084.
[BibTeX] [Link]

@InProceedings{karakos-et-al-2005,
author = "Damianos Karakos and Sanjeev Khudanpur and Jason
Eisner and Carey E. Priebe",
title = "Unsupervised Classification via Decision Trees: An
Information-Theoretic Perspective",
booktitle = "Proceedings of the 2005 IEEE International Conference
on Acoustics, Speech and Signal Processing (ICASSP)",
volume = "5",
pages = "1081--1084",
year = "2005",
month = mar,
address = "Philadelphia",
note = "Invited talk",
URL = "http://cs.jhu.edu/~jason/papers/#karakos-et-al-2005",
}

F. Masson, P. Julián, D. Puschini, P. Crocce, L. Arlenghi, A. Andreou, and P. Mandolesi, “Hybrid sensor network and fusion algorithm for sound source localization,” in 2005 IEEE International Symposium on Circuits and Systems, 2005.
[BibTeX] [Link]

@inproceedings{34076984,
title = {Hybrid sensor network and fusion algorithm for sound source localization},
author = {{F. Masson} and {P. Julián} and {D. Puschini} and {P. Crocce} and {L. Arlenghi} and {A. Andreou} and {P. Mandolesi}},
year = 2005,
month = {5},
booktitle = {2005 IEEE International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/d6e20e15223e3441e74ebb62e6306128baff7551},
}

J.M. Blain Christen and A. Andreou, “CMOS heater array for incubation environment cellular study,” in Midwest Symposium on Circuits and Systems, 2005.
[BibTeX] [Link]

@inproceedings{3051229,
title = {CMOS heater array for incubation environment cellular study},
author = {{J.M. Blain Christen} and {A. Andreou}},
year = 2005,
booktitle = {Midwest Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/413bbebc9f64ba8af7443fcb60ab27942ec140f6},
}

E. Culurciello, Thiago Teixeira, and A. Andreou, “Event-based imaging with active illumination in sensor networks,” in 2005 IEEE International Symposium on Circuits and Systems, 2005.
[BibTeX] [Link]

@inproceedings{8091076,
title = {Event-based imaging with active illumination in sensor networks},
author = {{E. Culurciello} and {Thiago Teixeira} and {A. Andreou}},
year = 2005,
month = {5},
booktitle = {2005 IEEE International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/fc32c185187bec2ea579554345c019aea13bda2b},
}

E. Culurciello and A. Andreou, “Capacitive coupling of data and power for 3D silicon-on-insulator VLSI,” in 2005 IEEE International Symposium on Circuits and Systems, 2005.
[BibTeX] [Link]

@inproceedings{8219009,
title = {Capacitive coupling of data and power for 3D silicon-on-insulator VLSI},
author = {{E. Culurciello} and {A. Andreou}},
year = 2005,
month = {5},
booktitle = {2005 IEEE International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/878f30c393ec0468c8de7d945580fcd1a28fae90},
}

P. Julián, A. Andreou, G. Cauwenberghs, M. Stanaćević, David H. Goldberg, P. Mandolesi, Laurence Riddle, and S. Shamma, “Field test results for low power bearing estimator sensor nodes,” in 2005 IEEE International Symposium on Circuits and Systems, 2005.
[BibTeX] [Link]

@inproceedings{10633458,
title = {Field test results for low power bearing estimator sensor nodes},
author = {{P. Julián} and {A. Andreou} and {G. Cauwenberghs} and {M. Stanaćević} and {David H. Goldberg} and {P. Mandolesi} and {Laurence Riddle} and {S. Shamma}},
year = 2005,
month = {5},
booktitle = {2005 IEEE International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/fdb5fbcd34502706f361c2014636a44b32ba3d78},
}

A. Apsel and A. Andreou, “A low-power silicon on sapphire CMOS optoelectronic receiver using low- and high-threshold devices,” in IEEE Transactions on Circuits and Systems Part 1: Regular Papers, 2005.
[BibTeX] [Link]

@inproceedings{3035508,
title = {A low-power silicon on sapphire CMOS optoelectronic receiver using low- and high-threshold devices},
author = {{A. Apsel} and {A. Andreou}},
year = 2005,
month = {2},
booktitle = {IEEE Transactions on Circuits and Systems Part 1: Regular Papers},
url = {https://www.semanticscholar.org/paper/e6f12c4fd211f6d31271618664eb6b31daf69bfd},
}

E. Culurciello, P. Pouliquen, A. Andreou, K. Strohbehn, and S. Jaskulek, “Monolithic digital galvanic isolation buffer fabricated in silicon on sapphire CMOS,” in Electronics Letters, 2005.
[BibTeX] [Link]

@inproceedings{109920157,
title = {Monolithic digital galvanic isolation buffer fabricated in silicon on sapphire CMOS},
author = {{E. Culurciello} and {P. Pouliquen} and {A. Andreou} and {K. Strohbehn} and {S. Jaskulek}},
year = 2005,
month = {4},
booktitle = {Electronics Letters},
url = {https://www.semanticscholar.org/paper/11077920601a5d4869703b0473bdab5cbd25e052},
}

E. Culurciello, P. Pouliquen, A. Andreou, K. Strohbehn, and S. Jaskulek, “A monolithic isolation amplifier in silicon-on-insulator CMOS,” in 2005 IEEE International Symposium on Circuits and Systems, 2005.
[BibTeX] [Link]

@inproceedings{26439714,
title = {A monolithic isolation amplifier in silicon-on-insulator CMOS},
author = {{E. Culurciello} and {P. Pouliquen} and {A. Andreou} and {K. Strohbehn} and {S. Jaskulek}},
year = 2005,
month = {5},
booktitle = {2005 IEEE International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/5cad0ae329636d2d5714afcd0121e7b03930e749},
}

M. Cohen, A. Andreou, A. Paulraj, D. Gore, R. Nabar, H. Bolcskei, G. Stuber, J. R. Barry, S. McLaughlin, Ye Li, Ingram, and M. A. Pratt, “Top Articles.” 2005.
[BibTeX] [Link]

@inproceedings{262502050,
title = {Top Articles},
author = {{M. Cohen} and {A. Andreou} and {A. Paulraj} and {D. Gore} and {R. Nabar} and {H. Bolcskei} and {G. Stuber} and {J. R. Barry} and {S. McLaughlin} and {Ye Li} and {Ingram} and {M. A. Pratt}},
year = 2005,
booktitle = {},
url = {https://www.semanticscholar.org/paper/773a8e9bfc5b8039d4a65d5a360ebf4e66503950},
}

G. Cauwenberghs, A. Andreou, J. West, M. Stanaćević, Abdullah Celik, P. Julián, Thiago Teixeira, C. Diehl, and Laurence Riddle, “A miniature low-power intelligent sensor node for persistent acoustic surveillance,” in SPIE Defense + Commercial Sensing, 2005.
[BibTeX] [Link]

@inproceedings{17301696,
title = {A miniature low-power intelligent sensor node for persistent acoustic surveillance},
author = {{G. Cauwenberghs} and {A. Andreou} and {J. West} and {M. Stanaćević} and {Abdullah Celik} and {P. Julián} and {Thiago Teixeira} and {C. Diehl} and {Laurence Riddle}},
year = 2005,
month = {5},
booktitle = {SPIE Defense + Commercial Sensing},
url = {https://www.semanticscholar.org/paper/af4e2125e4fe69992147b3ace38e39e6c4534a70},
}

E. Culurciello, P. Pouliquen, and A. Andreou, “Isolation charge pump fabricated in silicon on sapphire CMOS technology,” in Electronics Letters, 2005.
[BibTeX] [Link]

@inproceedings{110244379,
title = {Isolation charge pump fabricated in silicon on sapphire CMOS technology},
author = {{E. Culurciello} and {P. Pouliquen} and {A. Andreou}},
year = 2005,
month = {5},
booktitle = {Electronics Letters},
url = {https://www.semanticscholar.org/paper/93127462f2b89823f3bea93f252c49874391be45},
}

A. Kempe, J. Champarnaud, and Jason Eisner, “A Note on Join and Auto-Intersection of $n$-ary Rational Relations,” in Proceedings of the Eindhoven FASTAR Days (Computer Science Technical Report 04-40), 2004, p. 64–78.
[BibTeX] [Link]

@InProceedings{kempe-champarnaud-eisner-2004,
author = "Andr\'{e} Kempe and Jean-Marc Champarnaud and Jason
Eisner",
title = "A Note on Join and Auto-Intersection of $n$-ary
Rational Relations",
booktitle = "Proceedings of the Eindhoven FASTAR Days (Computer
Science Technical Report 04-40)",
editor = "Loek Cleophas and Bruce Watson",
pages = "64--78",
year = "2004",
month = dec,
organization = "Department of Mathematics and Computer Science,
Technische Universiteit Eindhoven, Netherlands",
URL = "http://cs.jhu.edu/~jason/papers/#kempe-champarnaud-eisner-2004",
}

J. Eisner, E. Goldlust, and N. A. Smith, “Dyna: A Declarative Language for Implementing Dynamic Programs,” in Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics (ACL), Companion Volume, Barcelona, 2004, p. 218–221.
[BibTeX] [Link]

@InProceedings{eisner-goldlust-smith-2004,
aclid = "P04-3032",
author = "Jason Eisner and Eric Goldlust and Noah A. Smith",
title = "Dyna: {A} Declarative Language for Implementing
Dynamic Programs",
booktitle = "Proceedings of the 42nd Annual Meeting of the
Association for Computational Linguistics (ACL),
Companion Volume",
pages = "218--221",
year = "2004",
month = jul,
address = "Barcelona",
URL = "http://cs.jhu.edu/~jason/papers/#eisner-goldlust-smith-2004",
}

N. A. Smith and J. Eisner, “Annealing Techniques for Unsupervised Statistical Language Learning,” in Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics (ACL), Barcelona, 2004, p. 486–493.
[BibTeX] [Link]

@InProceedings{smith-eisner-2004,
aclid = "P04-1062",
author = "Noah A. Smith and Jason Eisner",
title = "Annealing Techniques for Unsupervised Statistical
Language Learning",
booktitle = "Proceedings of the 42nd Annual Meeting of the
Association for Computational Linguistics (ACL)",
pages = "486--493",
year = "2004",
month = jul,
address = "Barcelona",
URL = "http://cs.jhu.edu/~jason/papers/#smith-eisner-2004",
}

A. Andreou, “A JSSC classic paper: Sigma-Delta converters,” in IEEE Solid-State Circuits Society Newsletter, 2004.
[BibTeX] [Link]

@inproceedings{41880831,
title = {A JSSC classic paper: Sigma-Delta converters},
author = {{A. Andreou}},
year = 2004,
booktitle = {IEEE Solid-State Circuits Society Newsletter},
url = {https://www.semanticscholar.org/paper/78d85e0625b4f36b6ca9c5ff9d3a148aec8e36e8},
}

E. Culurciello and A. Andreou, “A 16 × 16 pixel silicon on sapphire CMOS photosensor array with a digital interface for adaptive wavefront correction,” in International Symposium on Circuits and Systems, 2004.
[BibTeX] [Link]

@inproceedings{236460365,
title = {A 16 × 16 pixel silicon on sapphire CMOS photosensor array with a digital interface for adaptive wavefront correction},
author = {{E. Culurciello} and {A. Andreou}},
year = 2004,
booktitle = {International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/cf2be860f30ac5d7d621a1ceba3a7fb9340ba896},
}

P. Mandolesi, P. Julián, and A. Andreou, “A scalable and programmable simplicial CNN digital pixel processor architecture,” in IEEE Transactions on Circuits and Systems Part 1: Regular Papers, 2004.
[BibTeX] [Link]

@inproceedings{12260491,
title = {A scalable and programmable simplicial CNN digital pixel processor architecture},
author = {{P. Mandolesi} and {P. Julián} and {A. Andreou}},
year = 2004,
month = {5},
booktitle = {IEEE Transactions on Circuits and Systems Part 1: Regular Papers},
url = {https://www.semanticscholar.org/paper/3fb5574553e1c3ae6b4c48bd8c170da984a709a0},
}

A. Apsel, Zhongtao Fu, and A. Andreou, “A 2.5-mW SOS CMOS optical receiver for chip-to-chip interconnect,” in Journal of Lightwave Technology, 2004.
[BibTeX] [Link]

@inproceedings{31449595,
title = {A 2.5-mW SOS CMOS optical receiver for chip-to-chip interconnect},
author = {{A. Apsel} and {Zhongtao Fu} and {A. Andreou}},
year = 2004,
month = {9},
booktitle = {Journal of Lightwave Technology},
url = {https://www.semanticscholar.org/paper/d4211067322dc2a0df8236d703b390b036774c4b},
}

A. Andreou and David H. Goldberg, “Efficient spike communication and computation in biological and engineered systems.” 2004.
[BibTeX] [Link]

@inproceedings{63717901,
title = {Efficient spike communication and computation in biological and engineered systems},
author = {{A. Andreou} and {David H. Goldberg}},
year = 2004,
booktitle = {},
url = {https://www.semanticscholar.org/paper/4f7786d86a5d72c8194137e486ae7af00f52db49},
}

P. Mandolesi, P. Julián, and A. Andreou, “A simplicial CNN architecture for on-chip image processing,” in 2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512), 2004.
[BibTeX] [Link]

@inproceedings{31188038,
title = {A simplicial CNN architecture for on-chip image processing},
author = {{P. Mandolesi} and {P. Julián} and {A. Andreou}},
year = 2004,
month = {5},
booktitle = {2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512)},
url = {https://www.semanticscholar.org/paper/dd3d26b0cfc6db1c577aa499be83e446b1d9cd5e},
}

E. Culurciello and A. Andreou, “A 16 /spl times/ 16 pixel silicon on sapphire CMOS photosensor array with a digital interface for adaptive wavefront correction,” in 2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512), 2004.
[BibTeX] [Link]

@inproceedings{24950713,
title = {A 16 /spl times/ 16 pixel silicon on sapphire CMOS photosensor array with a digital interface for adaptive wavefront correction},
author = {{E. Culurciello} and {A. Andreou}},
year = 2004,
month = {5},
booktitle = {2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512)},
url = {https://www.semanticscholar.org/paper/f1863992cce1af15b1246986f1a100c92db2c1a1},
}

P. Julián, A. Andreou, Laurence Riddle, S. Shamma, David H. Goldberg, and G. Cauwenberghs, “A comparative study of sound localization algorithms for energy aware sensor network nodes,” in IEEE Transactions on Circuits and Systems Part 1: Regular Papers, 2004.
[BibTeX] [Link]

@inproceedings{6708545,
title = {A comparative study of sound localization algorithms for energy aware sensor network nodes},
author = {{P. Julián} and {A. Andreou} and {Laurence Riddle} and {S. Shamma} and {David H. Goldberg} and {G. Cauwenberghs}},
year = 2004,
month = {4},
booktitle = {IEEE Transactions on Circuits and Systems Part 1: Regular Papers},
url = {https://www.semanticscholar.org/paper/b7ec04aebae69ebc0bebb1bb8d7026b39452a2b0},
}

Francisco Tejada, A. Andreou, J. Miragliotta, R. Osiander, and D. Wesolek, “Silicon on sapphire CMOS architectures for interferometric array readout,” in 2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512), 2004.
[BibTeX] [Link]

@inproceedings{17231760,
title = {Silicon on sapphire CMOS architectures for interferometric array readout},
author = {{Francisco Tejada} and {A. Andreou} and {J. Miragliotta} and {R. Osiander} and {D. Wesolek}},
year = 2004,
month = {9},
booktitle = {2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512)},
url = {https://www.semanticscholar.org/paper/4fb38bc75018ca80a0b8826d954a3a1b5bc27a0d},
}

E. Culurciello and A. Andreou, “16/spl times/16 pixel silicon on sapphire CMOS digital pixel photosensor array,” in Electronics Letters, 2004.
[BibTeX] [Link]

@inproceedings{113530045,
title = {16/spl times/16 pixel silicon on sapphire CMOS digital pixel photosensor array},
author = {{E. Culurciello} and {A. Andreou}},
year = 2004,
month = {1},
booktitle = {Electronics Letters},
url = {https://www.semanticscholar.org/paper/2dc87534fa55d9ff535f66d28823d576d16656bc},
}

David H. Goldberg and A. Andreou, “Spike communication of dynamic stimuli: rate decoding versus temporal decoding,” in Neurocomputing, 2004.
[BibTeX] [Link]

@inproceedings{36350590,
title = {Spike communication of dynamic stimuli: rate decoding versus temporal decoding},
author = {{David H. Goldberg} and {A. Andreou}},
year = 2004,
month = {6},
booktitle = {Neurocomputing},
url = {https://www.semanticscholar.org/paper/4a550a5c7b6337110de6aab644967c82969cb472},
}

Francisco Tejada, D. Wesolek, J. Lehtonen, J. Miragliotta, A. Andreou, and R. Osiander, “An SOS MEMS interferometer,” in SPIE MOEMS-MEMS, 2004.
[BibTeX] [Link]

@inproceedings{120043495,
title = {An SOS MEMS interferometer},
author = {{Francisco Tejada} and {D. Wesolek} and {J. Lehtonen} and {J. Miragliotta} and {A. Andreou} and {R. Osiander}},
year = 2004,
month = {1},
booktitle = {SPIE MOEMS-MEMS},
url = {https://www.semanticscholar.org/paper/1ea3a55d626166368105787bae8553f6d654b280},
}

David H. Goldberg, A. Andreou, P. Julián, P. Pouliquen, Laurence Riddle, and Rich Rosasco, “A wake-up detector for an acoustic surveillance sensor network: algorithm and VLSI implementation,” in Third International Symposium on Information Processing in Sensor Networks, 2004. IPSN 2004, 2004.
[BibTeX] [Link]

@inproceedings{2599649,
title = {A wake-up detector for an acoustic surveillance sensor network: algorithm and VLSI implementation},
author = {{David H. Goldberg} and {A. Andreou} and {P. Julián} and {P. Pouliquen} and {Laurence Riddle} and {Rich Rosasco}},
year = 2004,
month = {4},
booktitle = {Third International Symposium on Information Processing in Sensor Networks, 2004. IPSN 2004},
url = {https://www.semanticscholar.org/paper/afc7898078b08930d18ad0c2181e68a719458fc6},
}

Francisco Tejada, A. Andreou, D. Wickenden, and A. Francomacaro, “Surface micromachining in Silicon on Sapphire CMOS technology,” in 2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512), 2004.
[BibTeX] [Link]

@inproceedings{5946240,
title = {Surface micromachining in Silicon on Sapphire CMOS technology},
author = {{Francisco Tejada} and {A. Andreou} and {D. Wickenden} and {A. Francomacaro}},
year = 2004,
month = {5},
booktitle = {2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512)},
url = {https://www.semanticscholar.org/paper/8c4e401e6086573a2defdbcd73426455cad26a38},
}

J. J. Liu, Z. Kalayjian, B. Riely, W. Chang, G. Simonis, A. Apsel, and A. Andreou, “Multichannel ultrathin silicon-on-sapphire optical interconnects,” in IEEE Journal of Selected Topics in Quantum Electronics, 2003.
[BibTeX] [Link]

@inproceedings{122758259,
title = {Multichannel ultrathin silicon-on-sapphire optical interconnects},
author = {{J. J. Liu} and {Z. Kalayjian} and {B. Riely} and {W. Chang} and {G. Simonis} and {A. Apsel} and {A. Andreou}},
year = 2003,
month = {10},
booktitle = {IEEE Journal of Selected Topics in Quantum Electronics},
url = {https://www.semanticscholar.org/paper/eb2ea5e1185cd3e70cffa630c12405c4c079cb1c},
}

J. Eisner, “Learning Non-Isomorphic Tree Mappings for Machine Translation,” in Proceedings of the 41st Annual Meeting of the Association for Computational Linguistics (ACL), Companion Volume, Sapporo, 2003, p. 205–208.
[BibTeX] [Link]

@InProceedings{eisner-2003-acl,
aclid = "P03-2041",
author = "Jason Eisner",
title = "Learning Non-Isomorphic Tree Mappings for Machine
Translation",
booktitle = "Proceedings of the 41st Annual Meeting of the
Association for Computational Linguistics (ACL),
Companion Volume",
pages = "205--208",
year = "2003",
month = jul,
address = "Sapporo",
URL = "http://cs.jhu.edu/~jason/papers/#eisner-2003-acl",
}

J. Eisner, “Simpler and More General Minimization for Weighted Finite-State Automata,” in Proceedings of the Joint Meeting of the Human Language Technology Conference and the North American Chapter of the Association for Computational Linguistics (HLT-NAACL), Edmonton, 2003, p. 64–71.
[BibTeX] [Link]

@InProceedings{eisner-2003-hlt,
aclid = "N03-1009",
author = "Jason Eisner",
title = "Simpler and More General Minimization for Weighted
Finite-State Automata",
booktitle = "Proceedings of the Joint Meeting of the Human Language
Technology Conference and the North American Chapter of
the Association for Computational Linguistics
(HLT-NAACL)",
pages = "64--71",
year = "2003",
month = may,
address = "Edmonton",
URL = "http://cs.jhu.edu/~jason/papers/#eisner-2003-hlt",
}

E. Culurciello and A. Andreou, “An 8-bit, 1mW successive approximation ADC in SOI CMOS,” in Proceedings of the 2003 International Symposium on Circuits and Systems, 2003. ISCAS ’03., 2003.
[BibTeX] [Link]

@inproceedings{37397472,
title = {An 8-bit, 1mW successive approximation ADC in SOI CMOS},
author = {{E. Culurciello} and {A. Andreou}},
year = 2003,
month = {5},
booktitle = {Proceedings of the 2003 International Symposium on Circuits and Systems, 2003. ISCAS '03.},
url = {https://www.semanticscholar.org/paper/5b8e5af2063e4316296244353854ca8363f57a58},
}

E. Culurciello and A. Andreou, “A comparative study of access topologies for chip-level address-event communication channels,” in IEEE Trans. Neural Networks, 2003.
[BibTeX] [Link]

@inproceedings{21766789,
title = {A comparative study of access topologies for chip-level address-event communication channels},
author = {{E. Culurciello} and {A. Andreou}},
year = 2003,
month = {9},
booktitle = {IEEE Trans. Neural Networks},
url = {https://www.semanticscholar.org/paper/8f1bfd136a506bca6be6b6b7bf427bfd37844971},
}

A. Apsel and A. Andreou, “A 7 milliwatt 1GBPS CMOS optical receiver for through wafer communication,” in Proceedings of the 2003 International Symposium on Circuits and Systems, 2003. ISCAS ’03., 2003.
[BibTeX] [Link]

@inproceedings{40026731,
title = {A 7 milliwatt 1GBPS CMOS optical receiver for through wafer communication},
author = {{A. Apsel} and {A. Andreou}},
year = 2003,
month = {5},
booktitle = {Proceedings of the 2003 International Symposium on Circuits and Systems, 2003. ISCAS '03.},
url = {https://www.semanticscholar.org/paper/a20e20995fbe939ea3b41645daea08459d2e31d4},
}

A. Apsel, E. Culurciello, A. Andreou, and K. Aliberti, “Thin film PIN photodiodes for optoelectronic silicon on sapphire CMOS,” in Proceedings of the 2003 International Symposium on Circuits and Systems, 2003. ISCAS ’03., 2003.
[BibTeX] [Link]

@inproceedings{2009128,
title = {Thin film PIN photodiodes for optoelectronic silicon on sapphire CMOS},
author = {{A. Apsel} and {E. Culurciello} and {A. Andreou} and {K. Aliberti}},
year = 2003,
month = {5},
booktitle = {Proceedings of the 2003 International Symposium on Circuits and Systems, 2003. ISCAS '03.},
url = {https://www.semanticscholar.org/paper/3b35f4c94262f6856d79158851b3825145c759da},
}

A. Apsel and A. Andreou, “Analysis of short distance optoelectronic link architectures,” in Proceedings of the 2003 International Symposium on Circuits and Systems, 2003. ISCAS ’03., 2003.
[BibTeX] [Link]

@inproceedings{35403518,
title = {Analysis of short distance optoelectronic link architectures},
author = {{A. Apsel} and {A. Andreou}},
year = 2003,
month = {5},
booktitle = {Proceedings of the 2003 International Symposium on Circuits and Systems, 2003. ISCAS '03.},
url = {https://www.semanticscholar.org/paper/31473674b33933ff83740bc21936f80fbec4122b},
}

N. Sgouros, A. Andreou, M. Sangriotis, P. Papageorgas, D. Maroulis, and NG Theofanous, “Compression of IP images for autostereoscopic 3D imaging applications,” in 3rd International Symposium on Image and Signal Processing and Analysis, 2003. ISPA 2003. Proceedings of the, 2003.
[BibTeX] [Link]

@inproceedings{14571038,
title = {Compression of IP images for autostereoscopic 3D imaging applications},
author = {{N. Sgouros} and {A. Andreou} and {M. Sangriotis} and {P. Papageorgas} and {D. Maroulis} and {NG Theofanous}},
year = 2003,
month = {9},
booktitle = {3rd International Symposium on Image and Signal Processing and Analysis, 2003. ISPA 2003. Proceedings of the},
url = {https://www.semanticscholar.org/paper/8c3f905a15cad55747b223abf0c61bbc91101adc},
}

P. Julián, A. Andreou, P. Mandolesi, and David H. Goldberg, “A low-power CMOS integrated circuit for bearing estimation,” in Proceedings of the 2003 International Symposium on Circuits and Systems, 2003. ISCAS ’03., 2003.
[BibTeX] [Link]

@inproceedings{30699245,
title = {A low-power CMOS integrated circuit for bearing estimation},
author = {{P. Julián} and {A. Andreou} and {P. Mandolesi} and {David H. Goldberg}},
year = 2003,
month = {5},
booktitle = {Proceedings of the 2003 International Symposium on Circuits and Systems, 2003. ISCAS '03.},
url = {https://www.semanticscholar.org/paper/8ed454310941f4a4a68f6941256bcd0efd90c22a},
}

B. Linares-Barranco, A. Andreou, G. Indiveri, and T. Shibata, “Guest editorial – Special issue on neural networks hardware implementations,” in IEEE Trans. Neural Networks, 2003.
[BibTeX] [Link]

@inproceedings{26975520,
title = {Guest editorial - Special issue on neural networks hardware implementations},
author = {{B. Linares-Barranco} and {A. Andreou} and {G. Indiveri} and {T. Shibata}},
year = 2003,
month = {9},
booktitle = {IEEE Trans. Neural Networks},
url = {https://www.semanticscholar.org/paper/f5513abf7b72220b9757b16342730748775f362e},
}

P. Julián, A. Andreou, Laurence Riddle, S. Shamma, and G. Cauwenberghs, “A comparison of algorithms for sound localization,” in Proceedings of the 2003 International Symposium on Circuits and Systems, 2003. ISCAS ’03., 2003.
[BibTeX] [Link]

@inproceedings{41499820,
title = {A comparison of algorithms for sound localization},
author = {{P. Julián} and {A. Andreou} and {Laurence Riddle} and {S. Shamma} and {G. Cauwenberghs}},
year = 2003,
month = {5},
booktitle = {Proceedings of the 2003 International Symposium on Circuits and Systems, 2003. ISCAS '03.},
url = {https://www.semanticscholar.org/paper/c6959240792e8cda2e324df58f68764d312b8f4c},
}

A. Apsel, Jiang Liu, A. Andreou, W. Chang, and G. Simonis, “Integrated arrays of low power SOS chip-to-chip interconnects for efficient parallel communication in CMOS.” 2003.
[BibTeX] [Link]

@inproceedings{111718664,
title = {Integrated arrays of low power SOS chip-to-chip interconnects for efficient parallel communication in CMOS},
author = {{A. Apsel} and {Jiang Liu} and {A. Andreou} and {W. Chang} and {G. Simonis}},
year = 2003,
month = {6},
booktitle = {},
url = {https://www.semanticscholar.org/paper/176cfdf52c792a258161fadc2e134c981749c01e},
}

David H. Goldberg, A. Sripati, and A. Andreou, “Energy efficiency in a channel model for the spiking axon,” in Neurocomputing, 2003.
[BibTeX] [Link]

@inproceedings{36729490,
title = {Energy efficiency in a channel model for the spiking axon},
author = {{David H. Goldberg} and {A. Sripati} and {A. Andreou}},
year = 2003,
month = {6},
booktitle = {Neurocomputing},
url = {https://www.semanticscholar.org/paper/a7110da29070e2fd2b5ad8fb76ceef9f0f8056d4},
}

A. Apsel and A. Andreou, “A 10 milliwatt 2 Gbps CMOS optical receiver for optoelectronic interconnect,” in Proceedings of the 2003 International Symposium on Circuits and Systems, 2003. ISCAS ’03., 2003.
[BibTeX] [Link]

@inproceedings{42004952,
title = {A 10 milliwatt 2 Gbps CMOS optical receiver for optoelectronic interconnect},
author = {{A. Apsel} and {A. Andreou}},
year = 2003,
month = {5},
booktitle = {Proceedings of the 2003 International Symposium on Circuits and Systems, 2003. ISCAS '03.},
url = {https://www.semanticscholar.org/paper/a58bd9def113605925c3e3a32c95df94a5f44223},
}

A. Andreou and Z. Kalayjian, “Polarization imaging: principles and integrated polarimeters,” in IEEE Sensors Journal, 2002.
[BibTeX] [Link]

@inproceedings{122879363,
title = {Polarization imaging: principles and integrated polarimeters},
author = {{A. Andreou} and {Z. Kalayjian}},
year = 2002,
month = {12},
booktitle = {IEEE Sensors Journal},
url = {https://www.semanticscholar.org/paper/08912d533bdc5a6e259bb5c3cb1e76a990be1580},
}

J. Eisner, “Parameter Estimation for Probabilistic Finite-State Transducers,” in Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics (ACL), Philadelphia, 2002, p. 1–8.
[BibTeX] [Link]

@InProceedings{eisner-2002-acl-fst,
aclid = "P02-1001",
author = "Jason Eisner",
title = "Parameter Estimation for Probabilistic Finite-State
Transducers",
booktitle = "Proceedings of the 40th Annual Meeting of the
Association for Computational Linguistics (ACL)",
pages = "1--8",
year = "2002",
month = jul,
address = "Philadelphia",
URL = "http://cs.jhu.edu/~jason/papers/#eisner-2002-acl-fst",
}

J. Eisner, “Comprehension and Compilation in Optimality Theory,” in Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics (ACL), Philadelphia, 2002, p. 56–63.
[BibTeX] [Link]

@InProceedings{eisner-2002-acl-ot,
aclid = "P02-1008",
author = "Jason Eisner",
title = "Comprehension and Compilation in {O}ptimality
{T}heory",
booktitle = "Proceedings of the 40th Annual Meeting of the
Association for Computational Linguistics (ACL)",
pages = "56--63",
year = "2002",
month = jul,
address = "Philadelphia",
URL = "http://cs.jhu.edu/~jason/papers/#eisner-2002-acl-ot",
}

J. Eisner, “An Interactive Spreadsheet for Teaching the Forward-Backward Algorithm,” in Proceedings of the ACL Workshop on Effective Tools and Methodologies for Teaching NLP and CL, Philadelphia, 2002, p. 10–18.
[BibTeX] [Link]

@InProceedings{eisner-2002-tnlp,
aclid = "W02-0102",
author = "Jason Eisner",
title = "An Interactive Spreadsheet for Teaching the
Forward-Backward Algorithm",
booktitle = "Proceedings of the ACL Workshop on Effective Tools and
Methodologies for Teaching NLP and CL",
editor = "Dragomir Radev and Chris Brew",
pages = "10--18",
year = "2002",
month = jul,
address = "Philadelphia",
URL = "http://cs.jhu.edu/~jason/papers/#eisner-2002-tnlp",
}

J. Eisner, “Transformational Priors Over Grammars,” in Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Philadelphia, 2002, p. 63–70.
[BibTeX] [Link]

@InProceedings{eisner-2002-emnlp,
aclid = "W02-1009",
author = "Jason Eisner",
title = "Transformational Priors Over Grammars",
booktitle = "Proceedings of the Conference on Empirical Methods in
Natural Language Processing (EMNLP)",
pages = "63--70",
year = "2002",
month = jul,
address = "Philadelphia",
note = "Nominated for Best Paper Award.",
URL = "http://cs.jhu.edu/~jason/papers/#eisner-2002-emnlp",
}

E. Culurciello, A. Andreou, and P. Pouliquen, “Modeling hot-electrons effects in silicon-on-sapphire MOSFETs,” in IEEE International Symposium on Circuits and Systems proceedings, 2002.
[BibTeX] [Link]

@inproceedings{15662068,
title = {Modeling hot-electrons effects in silicon-on-sapphire MOSFETs},
author = {{E. Culurciello} and {A. Andreou} and {P. Pouliquen}},
year = 2002,
month = {8},
booktitle = {IEEE International Symposium on Circuits and Systems proceedings},
url = {https://www.semanticscholar.org/paper/9dc4fb378b646999a9589c09f0c824b9ab38e1a7},
}

A. Apsel, A. Andreou, and J. Liu, “A 6 channel array of 5 milliwatt, 500 MHz optical receivers in .5 /spl mu/m SOS CMOS,” in IEEE International Symposium on Circuits and Systems proceedings, 2002.
[BibTeX] [Link]

@inproceedings{21149766,
title = {A 6 channel array of 5 milliwatt, 500 MHz optical receivers in .5 /spl mu/m SOS CMOS},
author = {{A. Apsel} and {A. Andreou} and {J. Liu}},
year = 2002,
month = {8},
booktitle = {IEEE International Symposium on Circuits and Systems proceedings},
url = {https://www.semanticscholar.org/paper/fd80450ae8cadd7d435fd065a436f636976c1d5a},
}

J. Christen, Cristina E. Davis, Min Li, and A. Andreou, “Design, double sided post-processing, and packaging of CMOS compatible bio-MEMS device arrays,” in IEEE International Symposium on Circuits and Systems proceedings, 2002.
[BibTeX] [Link]

@inproceedings{32482235,
title = {Design, double sided post-processing, and packaging of CMOS compatible bio-MEMS device arrays},
author = {{J. Christen} and {Cristina E. Davis} and {Min Li} and {A. Andreou}},
year = 2002,
month = {8},
booktitle = {IEEE International Symposium on Circuits and Systems proceedings},
url = {https://www.semanticscholar.org/paper/2688d86b31663735cfde25445dfe0d1d645c31d9},
}

K. V. Dang, P. Pouliquen, M. Grenn, A. Andreou, Paul Blase, and Sanh Phu, “Low Cost Microbolometer Development Using Commercially Available CMOS Foundry Processes.” 2002.
[BibTeX] [Link]

@inproceedings{110543057,
title = {Low Cost Microbolometer Development Using Commercially Available CMOS Foundry Processes},
author = {{K. V. Dang} and {P. Pouliquen} and {M. Grenn} and {A. Andreou} and {Paul Blase} and {Sanh Phu}},
year = 2002,
booktitle = {},
url = {https://www.semanticscholar.org/paper/650c8ade0fc4aea7b908c04808653a1368553a65},
}

J. J. Liu, Z. Kalayjian, W. Chang, G. Simonis, A. Apsel, and A. Andreou, “Ultra-thin silicon-on-sapphire multi-channel optical interconnects,” in Conference on Lasers and Electro-Optics, 2002.
[BibTeX] [Link]

@inproceedings{117749207,
title = {Ultra-thin silicon-on-sapphire multi-channel optical interconnects},
author = {{J. J. Liu} and {Z. Kalayjian} and {W. Chang} and {G. Simonis} and {A. Apsel} and {A. Andreou}},
year = 2002,
month = {5},
booktitle = {Conference on Lasers and Electro-Optics},
url = {https://www.semanticscholar.org/paper/7dbbf1741af1475cc60f6c82b282477ce66be41f},
}

K. V. Dang, W. Blase, S. Horn, P. Pouliquen, A. Andreou, G. Cauwenberghs, and J. Caulfield, “Advanced on-FPA signal processing for staring IRFPAs,” in SPIE Optics + Photonics, 2001.
[BibTeX] [Link]

@inproceedings{109277592,
title = {Advanced on-FPA signal processing for staring IRFPAs},
author = {{K. V. Dang} and {W. Blase} and {S. Horn} and {P. Pouliquen} and {A. Andreou} and {G. Cauwenberghs} and {J. Caulfield}},
year = 2001,
month = {12},
booktitle = {SPIE Optics + Photonics},
url = {https://www.semanticscholar.org/paper/a153cc97b70dab9758d9f280b577530fb7c4bad8},
}

M. Martin, D. Roth, A. Garrison-Darrin, P. Mcnulty, and A. Andreou, “FGMOS dosimetry: design and implementation,” in IEEE Transactions on Nuclear Science, 2001.
[BibTeX] [Link]

@inproceedings{111368078,
title = {FGMOS dosimetry: design and implementation},
author = {{M. Martin} and {D. Roth} and {A. Garrison-Darrin} and {P. Mcnulty} and {A. Andreou}},
year = 2001,
month = {12},
booktitle = {IEEE Transactions on Nuclear Science},
url = {https://www.semanticscholar.org/paper/a7756dd74fd6ea1610f1fa81ff8d601ea4965111},
}

A. Apsel and A. Andreou, “Analysis of data reconstruction efficiency using stochastic encoding and an integrating receiver,” in IEEE Transactions on Circuits and Systems Ii: Analog and Digital Signal Processing, 2001.
[BibTeX] [Link]

@inproceedings{62316916,
title = {Analysis of data reconstruction efficiency using stochastic encoding and an integrating receiver},
author = {{A. Apsel} and {A. Andreou}},
year = 2001,
month = {10},
booktitle = {IEEE Transactions on Circuits and Systems Ii: Analog and Digital Signal Processing},
url = {https://www.semanticscholar.org/paper/6dd2419df16eb7d0f3f2a2e0f807ead86a48623c},
}

J. Eisner, “Expectation Semirings: Flexible EM for Finite-State Transducers,” in Proceedings of the ESSLLI Workshop on Finite-State Methods in Natural Language Processing (FSMNLP), Helsinki, 2001.
[BibTeX] [Link]

@InProceedings{eisner-2001-fsmnlp,
author = "Jason Eisner",
title = "Expectation Semirings: Flexible {EM} for Finite-State
Transducers",
booktitle = "Proceedings of the ESSLLI Workshop on Finite-State
Methods in Natural Language Processing (FSMNLP)",
editor = "Gertjan van Noord",
year = "2001",
month = aug,
address = "Helsinki",
note = "Extended abstract (5 pages)",
URL = "http://cs.jhu.edu/~jason/papers/#eisner-2001-fsmnlp",
}

A. Andreou, David H. Goldberg, E. Culurciello, M. Stanaćević, G. Cauwenberghs, and Laurence Riddle, “Heterogeneous integration of biomimetic acoustic microsystems,” in ISCAS 2001. The 2001 IEEE International Symposium on Circuits and Systems (Cat. No.01CH37196), 2001.
[BibTeX] [Link]

@inproceedings{16600244,
title = {Heterogeneous integration of biomimetic acoustic microsystems},
author = {{A. Andreou} and {David H. Goldberg} and {E. Culurciello} and {M. Stanaćević} and {G. Cauwenberghs} and {Laurence Riddle}},
year = 2001,
month = {5},
booktitle = {ISCAS 2001. The 2001 IEEE International Symposium on Circuits and Systems (Cat. No.01CH37196)},
url = {https://www.semanticscholar.org/paper/ce603e5e19380c3437f561c676e72db0af6aabad},
}

A. Apsel and A. Andreou, “5 mV, Gbit/s silicon on sapphire CMOS optical receiver,” in Electronics Letters, 2001.
[BibTeX] [Link]

@inproceedings{111207115,
title = {5 mV, Gbit/s silicon on sapphire CMOS optical receiver},
author = {{A. Apsel} and {A. Andreou}},
year = 2001,
month = {9},
booktitle = {Electronics Letters},
url = {https://www.semanticscholar.org/paper/e5247a91c2cacdb3821f4bc1f18731b8dba09be6},
}

David H. Goldberg, G. Cauwenberghs, and A. Andreou, “Probabilistic synaptic weighting in a reconfigurable network of VLSI integrate-and-fire neurons,” in Neural Networks, 2001.
[BibTeX] [Link]

@inproceedings{7913359,
title = {Probabilistic synaptic weighting in a reconfigurable network of VLSI integrate-and-fire neurons},
author = {{David H. Goldberg} and {G. Cauwenberghs} and {A. Andreou}},
year = 2001,
month = {7},
booktitle = {Neural Networks},
url = {https://www.semanticscholar.org/paper/6d3fa11af0d13120c2bb941b04a2982ca3fc9561},
}

P. Abshire and A. Andreou, “A communication channel model for information transmission in the blowfly photoreceptor.,” in Bio Systems, 2001.
[BibTeX] [Link]

@inproceedings{18742393,
title = {A communication channel model for information transmission in the blowfly photoreceptor.},
author = {{P. Abshire} and {A. Andreou}},
year = 2001,
month = {9},
booktitle = {Bio Systems},
url = {https://www.semanticscholar.org/paper/a4c5f83ffc31e969d4eeed09dca205cc2ec05bba},
}

A. Apsel and A. Andreou, “Analysis of Data Reconstruction Efficiency Using.” 2001.
[BibTeX] [Link]

@inproceedings{61453218,
title = {Analysis of Data Reconstruction Efficiency Using},
author = {{A. Apsel} and {A. Andreou}},
year = 2001,
booktitle = {},
url = {https://www.semanticscholar.org/paper/58faa289c89dc0142f499304fb733d8aa47e1448},
}

David H. Goldberg, G. Cauwenberghs, and A. Andreou, “Analog VLSI spiking neural network with address domain probabilistic synapses,” in ISCAS 2001. The 2001 IEEE International Symposium on Circuits and Systems (Cat. No.01CH37196), 2001.
[BibTeX] [Link]

@inproceedings{8543826,
title = {Analog VLSI spiking neural network with address domain probabilistic synapses},
author = {{David H. Goldberg} and {G. Cauwenberghs} and {A. Andreou}},
year = 2001,
month = {5},
booktitle = {ISCAS 2001. The 2001 IEEE International Symposium on Circuits and Systems (Cat. No.01CH37196)},
url = {https://www.semanticscholar.org/paper/362209d46dba3b59fdd2bc1b19576dfc84fbb1ae},
}

A. Andreou, Z. Kalayjian, A. Apsel, P. Pouliquen, R. Athale, G. Simonis, and R. Reedy, “Silicon on sapphire CMOS for optoelectronic microsystems,” in IEEE Circuits and Systems Magazine, 2001.
[BibTeX] [Link]

@inproceedings{62480671,
title = {Silicon on sapphire CMOS for optoelectronic microsystems},
author = {{A. Andreou} and {Z. Kalayjian} and {A. Apsel} and {P. Pouliquen} and {R. Athale} and {G. Simonis} and {R. Reedy}},
year = 2001,
booktitle = {IEEE Circuits and Systems Magazine},
url = {https://www.semanticscholar.org/paper/b5d04538a5b139ad3596eb14e0e580abc0e23e99},
}

P. Abshire and A. Andreou, “Capacity and energy cost of information in biological and silicon photoreceptors,” in Proceedings of the IEEE, 2001.
[BibTeX] [Link]

@inproceedings{12766130,
title = {Capacity and energy cost of information in biological and silicon photoreceptors},
author = {{P. Abshire} and {A. Andreou}},
year = 2001,
month = {7},
booktitle = {Proceedings of the IEEE},
url = {https://www.semanticscholar.org/paper/59fa1c04cd742c545aec64ac0f0a22373f39fe1c},
}

G. Simonis, Z. Kalayjian, A. Apsel, P. Pouliquen, A. Andreou, R. Athale, and R. Reedy, “Silicon-on-sapphire CMOS for improved VCSEL/CMOS optoelectronic interconnects,” in LEOS 2000. 2000 IEEE Annual Meeting Conference Proceedings. 13th Annual Meeting. IEEE Lasers and Electro-Optics Society 2000 Annual Meeting (Cat. No.00CH37080), 2000.
[BibTeX] [Link]

@inproceedings{124920278,
title = {Silicon-on-sapphire CMOS for improved VCSEL/CMOS optoelectronic interconnects},
author = {{G. Simonis} and {Z. Kalayjian} and {A. Apsel} and {P. Pouliquen} and {A. Andreou} and {R. Athale} and {R. Reedy}},
year = 2000,
month = {11},
booktitle = {LEOS 2000. 2000 IEEE Annual Meeting Conference Proceedings. 13th Annual Meeting. IEEE Lasers and Electro-Optics Society 2000 Annual Meeting (Cat. No.00CH37080)},
url = {https://www.semanticscholar.org/paper/f495d04ff6fcf4e289f6a6c54882fd551562789f},
}

J. Eisner, “Easy and Hard Constraint Ranking in Optimality Theory: Algorithms and Complexity,” in Finite-State Phonology: Proceedings of the 5th Workshop of the ACL Special Interest Group in Computational Phonology (SIGPHON), Luxembourg, 2000, p. 22–33.
[BibTeX] [Link]

@InProceedings{eisner-2000-sigphon,
aclid = "W00-1803",
author = "Jason Eisner",
title = "Easy and Hard Constraint Ranking in {O}ptimality
{T}heory: Algorithms and Complexity",
booktitle = "Finite-State Phonology: Proceedings of the 5th
Workshop of the ACL Special Interest Group in
Computational Phonology (SIGPHON)",
editor = "Jason Eisner and Lauri Karttunen and Alain
Th\'{e}riault",
pages = "22--33",
year = "2000",
month = aug,
address = "Luxembourg",
URL = "http://cs.jhu.edu/~jason/papers/#eisner-2000-sigphon",
}

J. Eisner, “Directional Constraint Evaluation in Optimality Theory,” in Proceedings of the 18th International Conference on Computational Linguistics (COLING 2000), Saarbrücken, Germany, 2000, p. 257–263.
[BibTeX] [Link]

@InProceedings{eisner-2000-coling,
aclid = "C00-1038",
author = "Jason Eisner",
title = "Directional Constraint Evaluation in {O}ptimality
{T}heory",
booktitle = "Proceedings of the 18th International Conference on
Computational Linguistics (COLING 2000)",
pages = "257--263",
year = "2000",
month = aug,
address = "Saarbr{\"{u}}cken, Germany",
URL = "http://cs.jhu.edu/~jason/papers/#eisner-2000-coling",
}

J. Eisner and G. Satta, “A Faster Parsing Algorithm for Lexicalized Tree-Adjoining Grammars,” in Proceedings of the 5th Workshop on Tree-Adjoining Grammars and Related Formalisms (TAG+5), Paris, 2000, p. 14–19.
[BibTeX] [Link]

@InProceedings{eisner-satta-2000,
author = "Jason Eisner and Giorgio Satta",
title = "A Faster Parsing Algorithm for Lexicalized
Tree-Adjoining Grammars",
booktitle = "Proceedings of the 5th Workshop on Tree-Adjoining
Grammars and Related Formalisms (TAG+5)",
pages = "14--19",
year = "2000",
month = may,
address = "Paris",
URL = "http://cs.jhu.edu/~jason/papers/#eisner-satta-2000",
}

T. Serrano-Gotarredona, A. Andreou, and B. Linares-Barranco, “A Programmable VLSI Filter Architecture for Application in Real-Time Vision Processing Systems,” in International Journal of Neural Systems, 2000.
[BibTeX] [Link]

@inproceedings{8910256,
title = {A Programmable VLSI Filter Architecture for Application in Real-Time Vision Processing Systems},
author = {{T. Serrano-Gotarredona} and {A. Andreou} and {B. Linares-Barranco}},
year = 2000,
month = {6},
booktitle = {International Journal of Neural Systems},
url = {https://www.semanticscholar.org/paper/48789f24d44bf6e9f9560b0e003181e743e4a216},
}

A. Andreou and Z. Kalayjian, “Vlseye: optoelectronic vision and image processing.” 2000.
[BibTeX] [Link]

@inproceedings{137727200,
title = {Vlseye: optoelectronic vision and image processing},
author = {{A. Andreou} and {Z. Kalayjian}},
year = 2000,
booktitle = {},
url = {https://www.semanticscholar.org/paper/c4a6295961026a51f5f9284b650e1b65e0c09342},
}

Z. Kalayjian and A. Andreou, “Mismatch in photodiode and phototransistor arrays,” in 2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353), 2000.
[BibTeX] [Link]

@inproceedings{1697748,
title = {Mismatch in photodiode and phototransistor arrays},
author = {{Z. Kalayjian} and {A. Andreou}},
year = 2000,
month = {5},
booktitle = {2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353)},
url = {https://www.semanticscholar.org/paper/c410d1baa3730be9061f8365ddcf0a551cebb398},
}

A. Apsel, Z. Kalayjian, A. Andreou, G. Simonis, W. Chang, M. Datta, and B. Koley, “Edge orientation enhancement using optoelectronic VLSI and asynchronous pulse coding,” in 2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353), 2000.
[BibTeX] [Link]

@inproceedings{34180914,
title = {Edge orientation enhancement using optoelectronic VLSI and asynchronous pulse coding},
author = {{A. Apsel} and {Z. Kalayjian} and {A. Andreou} and {G. Simonis} and {W. Chang} and {M. Datta} and {B. Koley}},
year = 2000,
month = {5},
booktitle = {2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353)},
url = {https://www.semanticscholar.org/paper/7a906d3f2b1e42fe8e1ac30dd6b932eeda158cc8},
}

T. Serrano-Gotarredona, B. Linares-Barranco, and A. Andreou, “Programmable kernel analog VLSI convolution chip for real time vision processing,” in Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium, 2000.
[BibTeX] [Link]

@inproceedings{16406006,
title = {Programmable kernel analog VLSI convolution chip for real time vision processing},
author = {{T. Serrano-Gotarredona} and {B. Linares-Barranco} and {A. Andreou}},
year = 2000,
month = {7},
booktitle = {Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium},
url = {https://www.semanticscholar.org/paper/2028231bfa92a0c3442841aba3cf3215f65c8f39},
}

P. Pouliquen, A. Andreou, G. Cauwenberghs, and C. Terrill, “A CMOS smart focal plane for infra-red imagers,” in 2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353), 2000.
[BibTeX] [Link]

@inproceedings{22665701,
title = {A CMOS smart focal plane for infra-red imagers},
author = {{P. Pouliquen} and {A. Andreou} and {G. Cauwenberghs} and {C. Terrill}},
year = 2000,
month = {5},
booktitle = {2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353)},
url = {https://www.semanticscholar.org/paper/0174ca75074700bbe739e1b5fd8ab6c67848895e},
}

A. Apsel and A. Andreou, “Quality of data reconstruction using stochastic encoding and an integrating receiver,” in Proceedings of the 43rd IEEE Midwest Symposium on Circuits and Systems (Cat.No.CH37144), 2000.
[BibTeX] [Link]

@inproceedings{62621220,
title = {Quality of data reconstruction using stochastic encoding and an integrating receiver},
author = {{A. Apsel} and {A. Andreou}},
year = 2000,
month = {8},
booktitle = {Proceedings of the 43rd IEEE Midwest Symposium on Circuits and Systems (Cat.No.CH37144)},
url = {https://www.semanticscholar.org/paper/76260cc1e28e877572e276f8c76e545c5f260158},
}

W. Millard, Z. Kalayjian, and A. Andreou, “Calibration and matching of floating gate devices,” in 2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353), 2000.
[BibTeX] [Link]

@inproceedings{8853356,
title = {Calibration and matching of floating gate devices},
author = {{W. Millard} and {Z. Kalayjian} and {A. Andreou}},
year = 2000,
month = {5},
booktitle = {2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353)},
url = {https://www.semanticscholar.org/paper/d80a1ac766852437a76641d553c23de13972d6b4},
}

P. Abshire and A. Andreou, “Relating information capacity to a biophysical model for blowfly photoreceptors,” in Neurocomputing, 2000.
[BibTeX] [Link]

@inproceedings{19011322,
title = {Relating information capacity to a biophysical model for blowfly photoreceptors},
author = {{P. Abshire} and {A. Andreou}},
year = 2000,
month = {6},
booktitle = {Neurocomputing},
url = {https://www.semanticscholar.org/paper/06cf0ef7b747127404fd0376648ca1409b69705f},
}

T. Serrano-Gotarredona, B. Linares-Barranco, and A. Andreou, “Very Wide Range Tunable CMOS/Bipolar Current Mirrors with Voltage Clamped Input.” 1999.
[BibTeX] [Link]

@inproceedings{6885978,
title = {Very Wide Range Tunable CMOS/Bipolar Current Mirrors with Voltage Clamped Input},
author = {{T. Serrano-Gotarredona} and {B. Linares-Barranco} and {A. Andreou}},
year = 1999,
month = {11},
booktitle = {},
url = {https://www.semanticscholar.org/paper/3433e9342bdd76df0acf4085f0b080ffc4759ce0},
}

J. Eisner and G. Satta, “Efficient Parsing for Bilexical Context-Free Grammars and Head-Automaton Grammars,” in Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics (ACL), University of Maryland, 1999, p. 457–464.
[BibTeX] [Link]

@InProceedings{eisner-satta-1999,
aclid = "P99-1059",
author = "Jason Eisner and Giorgio Satta",
title = "Efficient Parsing for Bilexical Context-Free Grammars
and Head-Automaton Grammars",
booktitle = "Proceedings of the 37th Annual Meeting of the
Association for Computational Linguistics (ACL)",
pages = "457--464",
year = "1999",
month = jun,
address = "University of Maryland",
URL = "http://cs.jhu.edu/~jason/papers/#eisner-satta-1999",
}

E. Sánchez-Sinencio and A. Andreou, “LowVoltage Circuit Techniques Using FloatingGate Transistors.” 1999.
[BibTeX] [Link]

@inproceedings{111217965,
title = {LowVoltage Circuit Techniques Using FloatingGate Transistors},
author = {{E. Sánchez-Sinencio} and {A. Andreou}},
year = 1999,
booktitle = {},
url = {https://www.semanticscholar.org/paper/1e6d564e8d25876aeb82bd153711106320f3ee09},
}

E. Sánchez-Sinencio and A. Andreou, “LowVoltage Analog CMOS Filter Design.” 1999.
[BibTeX] [Link]

@inproceedings{62427511,
title = {LowVoltage Analog CMOS Filter Design},
author = {{E. Sánchez-Sinencio} and {A. Andreou}},
year = 1999,
booktitle = {},
url = {https://www.semanticscholar.org/paper/1021bbcd1db8d890e04b3ef505e68f7e1f6eac68},
}

T. Serrano-Gotarredona, A. Andreou, and B. Linares-Barranco, “AER image filtering architecture for vision-processing systems,” in IEEE Transactions on Circuits and Systems I-regular Papers, 1999.
[BibTeX] [Link]

@inproceedings{3641670,
title = {AER image filtering architecture for vision-processing systems},
author = {{T. Serrano-Gotarredona} and {A. Andreou} and {B. Linares-Barranco}},
year = 1999,
month = {9},
booktitle = {IEEE Transactions on Circuits and Systems I-regular Papers},
url = {https://www.semanticscholar.org/paper/779367e5f41dbf67cffa65e7ad127f560278a898},
}

E. Sánchez-Sinencio and A. Andreou, “LowVoltage/LowPower Amplifiers with Optimized Dynamic Range and Bandwidth.” 1999.
[BibTeX] [Link]

@inproceedings{61574052,
title = {LowVoltage/LowPower Amplifiers with Optimized Dynamic Range and Bandwidth},
author = {{E. Sánchez-Sinencio} and {A. Andreou}},
year = 1999,
booktitle = {},
url = {https://www.semanticscholar.org/paper/31f0a43e4b3530960d6bf6a33f8736cb48753336},
}

E. Sánchez-Sinencio and A. Andreou, “Low-voltage/low-power integrated circuits and systems : low-voltage mixed-signal circuits.” 1999.
[BibTeX] [Link]

@inproceedings{58156152,
title = {Low-voltage/low-power integrated circuits and systems : low-voltage mixed-signal circuits},
author = {{E. Sánchez-Sinencio} and {A. Andreou}},
year = 1999,
booktitle = {},
url = {https://www.semanticscholar.org/paper/d33dd6678be4868da708c5e8f673634aea37efe1},
}

E. Sánchez-Sinencio and A. Andreou, “LowPower Multiplierless YUVtoRGB Converter Based on Human Vision Perception.” 1999.
[BibTeX] [Link]

@inproceedings{61922489,
title = {LowPower Multiplierless YUVtoRGB Converter Based on Human Vision Perception},
author = {{E. Sánchez-Sinencio} and {A. Andreou}},
year = 1999,
booktitle = {},
url = {https://www.semanticscholar.org/paper/96064ae9348fbc9ccfb05b0ddd2b1273c172e4b7},
}

E. Sánchez-Sinencio and A. Andreou, “A Synchronous GatedClock Strategy for LowPower Design of Telecom ASICs.” 1999.
[BibTeX] [Link]

@inproceedings{110312024,
title = {A Synchronous GatedClock Strategy for LowPower Design of Telecom ASICs},
author = {{E. Sánchez-Sinencio} and {A. Andreou}},
year = 1999,
booktitle = {},
url = {https://www.semanticscholar.org/paper/5dfa5f118ca2cd72292a3fdf9da8ca68616c56d8},
}

E. Sánchez-Sinencio and A. Andreou, “An Information Theoretic Framework for Comparing the Bit Energy of Signal Representations at the Circuit Level.” 1999.
[BibTeX] [Link]

@inproceedings{123603313,
title = {An Information Theoretic Framework for Comparing the Bit Energy of Signal Representations at the Circuit Level},
author = {{E. Sánchez-Sinencio} and {A. Andreou}},
year = 1999,
booktitle = {},
url = {https://www.semanticscholar.org/paper/374d8ffabbc8c89080b608ec098dadb966e198a6},
}

E. Sánchez-Sinencio and A. Andreou, “Exploiting Device Physics in Circuit Design for Efficient Computational Functions in Analog VLSI.” 1999.
[BibTeX] [Link]

@inproceedings{30161288,
title = {Exploiting Device Physics in Circuit Design for Efficient Computational Functions in Analog VLSI},
author = {{E. Sánchez-Sinencio} and {A. Andreou}},
year = 1999,
booktitle = {},
url = {https://www.semanticscholar.org/paper/2c6875c31ba1f64132534cba1885019be39c10b0},
}

T. Serrano-Gotarredona, B. Linares-Barranco, and A. Andreou, “Bipolar/CMOS current-source flip-flop for application in neuro-fuzzy systems,” in Electronics Letters, 1999.
[BibTeX] [Link]

@inproceedings{110562712,
title = {Bipolar/CMOS current-source flip-flop for application in neuro-fuzzy systems},
author = {{T. Serrano-Gotarredona} and {B. Linares-Barranco} and {A. Andreou}},
year = 1999,
month = {8},
booktitle = {Electronics Letters},
url = {https://www.semanticscholar.org/paper/995bfe41821b641e8070f201d67d86f1014304b6},
}

S. Edgar and A. Andreou, “Low-Voltage/Low-Power Integrated Circuits and Systems.” 1999.
[BibTeX] [Link]

@inproceedings{57477236,
title = {Low-Voltage/Low-Power Integrated Circuits and Systems},
author = {{S. Edgar} and {A. Andreou}},
year = 1999,
booktitle = {},
url = {https://www.semanticscholar.org/paper/9e48131b4bdfcb5f748f72a54d418d86d566128c},
}

T. Serrano-Gotarredona, B. Linares-Barranco, and A. Andreou, “A General Translinear Principle for Subthreshold MOS Transistors.” 1999.
[BibTeX] [Link]

@inproceedings{6299332,
title = {A General Translinear Principle for Subthreshold MOS Transistors},
author = {{T. Serrano-Gotarredona} and {B. Linares-Barranco} and {A. Andreou}},
year = 1999,
month = {5},
booktitle = {},
url = {https://www.semanticscholar.org/paper/fc0a27ea73e36944029dd19ee16a346ca947943c},
}

E. Sánchez-Sinencio and A. Andreou, “LowPower CMOS Data Conversion.” 1999.
[BibTeX] [Link]

@inproceedings{61667078,
title = {LowPower CMOS Data Conversion},
author = {{E. Sánchez-Sinencio} and {A. Andreou}},
year = 1999,
booktitle = {},
url = {https://www.semanticscholar.org/paper/a80364aac3891a167baec08cd6044165b80f95f1},
}

P. Pouliquen, A. Andreou, G. Cauwenberghs, and C. Terrill, “Learning to compensate for sensor variability at the focal plane,” in IJCNN’99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339), 1999.
[BibTeX] [Link]

@inproceedings{35432293,
title = {Learning to compensate for sensor variability at the focal plane},
author = {{P. Pouliquen} and {A. Andreou} and {G. Cauwenberghs} and {C. Terrill}},
year = 1999,
month = {7},
booktitle = {IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339)},
url = {https://www.semanticscholar.org/paper/71a33fdd6c6a7ee4bd3254ca275e73763e6b26fd},
}

E. Sánchez-Sinencio and A. Andreou, “LowVoltage CMOS Operational Amplifiers.” 1999.
[BibTeX] [Link]

@inproceedings{62507561,
title = {LowVoltage CMOS Operational Amplifiers},
author = {{E. Sánchez-Sinencio} and {A. Andreou}},
year = 1999,
booktitle = {},
url = {https://www.semanticscholar.org/paper/75acf24ef393fc9ec83109d2dd77285e96f61a19},
}

T. Serrano-Gotarredona, A. Andreou, and B. Linares-Barranco, “Programmable 2D image filter for AER vision processing,” in ICECS’99. Proceedings of ICECS ’99. 6th IEEE International Conference on Electronics, Circuits and Systems (Cat. No.99EX357), 1999.
[BibTeX] [Link]

@inproceedings{61145410,
title = {Programmable 2D image filter for AER vision processing},
author = {{T. Serrano-Gotarredona} and {A. Andreou} and {B. Linares-Barranco}},
year = 1999,
month = {9},
booktitle = {ICECS'99. Proceedings of ICECS '99. 6th IEEE International Conference on Electronics, Circuits and Systems (Cat. No.99EX357)},
url = {https://www.semanticscholar.org/paper/5ea4dc0b4a109d7f468dfafbbdf42c95f69f7a38},
}

E. Sánchez-Sinencio and A. Andreou, “A Review of the Performance of Available Integrated Circuit Components Under the Constraints of LowPower Operation.” 1999.
[BibTeX] [Link]

@inproceedings{62111478,
title = {A Review of the Performance of Available Integrated Circuit Components Under the Constraints of LowPower Operation},
author = {{E. Sánchez-Sinencio} and {A. Andreou}},
year = 1999,
booktitle = {},
url = {https://www.semanticscholar.org/paper/335b3f2999b63da6bb20d212218a6031a10578af},
}

Á. Rodríguez-Vázquez, T. Roska, and A. Andreou, “Guest Editorial Special Issue On Bio-inspired Processors And Cellular Neural Networks For Vision,” in IEEE Transactions on Circuits and Systems I-regular Papers, 1999.
[BibTeX] [Link]

@inproceedings{62541548,
title = {Guest Editorial Special Issue On Bio-inspired Processors And Cellular Neural Networks For Vision},
author = {{Á. Rodríguez-Vázquez} and {T. Roska} and {A. Andreou}},
year = 1999,
month = {2},
booktitle = {IEEE Transactions on Circuits and Systems I-regular Papers},
url = {https://www.semanticscholar.org/paper/6f2bea100be2230742a642b3513bb456edaf553e},
}

Z. Kalayjian and A. Andreou, “A silicon retina for polarization contrast vision,” in IJCNN’99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339), 1999.
[BibTeX] [Link]

@inproceedings{8179040,
title = {A silicon retina for polarization contrast vision},
author = {{Z. Kalayjian} and {A. Andreou}},
year = 1999,
month = {7},
booktitle = {IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339)},
url = {https://www.semanticscholar.org/paper/bd0fbdcb357650ba6f2fad71affcbdcf3903c5d5},
}

E. Sánchez-Sinencio and A. Andreou, “HighEfficiency LowVoltage DCDC Conversion for Portable Applications.” 1999.
[BibTeX] [Link]

@inproceedings{108940837,
title = {HighEfficiency LowVoltage DCDC Conversion for Portable Applications},
author = {{E. Sánchez-Sinencio} and {A. Andreou}},
year = 1999,
booktitle = {},
url = {https://www.semanticscholar.org/paper/5a8be5e7ca9621923e3a3596e766129f1797d26a},
}

T. Serrano-Gotarredona, A. Andreou, and B. Linares-Barranco, “Programmable 2D image filter for AER vision processing,” in ISCAS’99. Proceedings of the 1999 IEEE International Symposium on Circuits and Systems VLSI (Cat. No.99CH36349), 1999.
[BibTeX] [Link]

@inproceedings{21531828,
title = {Programmable 2D image filter for AER vision processing},
author = {{T. Serrano-Gotarredona} and {A. Andreou} and {B. Linares-Barranco}},
year = 1999,
month = {5},
booktitle = {ISCAS'99. Proceedings of the 1999 IEEE International Symposium on Circuits and Systems VLSI (Cat. No.99CH36349)},
url = {https://www.semanticscholar.org/paper/3dc72833b85cab838edaf843c82ec278cb4b3066},
}

A. Andreou, “Energy and information processing in biological and silicon sensory systems,” in Proceedings of the Seventh International Conference on Microelectronics for Neural, Fuzzy and Bio-Inspired Systems, 1999.
[BibTeX] [Link]

@inproceedings{60843611,
title = {Energy and information processing in biological and silicon sensory systems},
author = {{A. Andreou}},
year = 1999,
month = {4},
booktitle = {Proceedings of the Seventh International Conference on Microelectronics for Neural, Fuzzy and Bio-Inspired Systems},
url = {https://www.semanticscholar.org/paper/66d8d99457e22a31f2a5c27f8440a3bdee8f6d00},
}

E. Sánchez-Sinencio and A. Andreou, “ContinuousTime LowVoltage CurrentMode Filters.” 1999.
[BibTeX] [Link]

@inproceedings{177306889,
title = {ContinuousTime LowVoltage CurrentMode Filters},
author = {{E. Sánchez-Sinencio} and {A. Andreou}},
year = 1999,
booktitle = {},
url = {https://www.semanticscholar.org/paper/c7a45fd62987870faa2342fe365a00364f1bfb32},
}

E. Sánchez-Sinencio and A. Andreou, “A CurrentBased MOSFET Model for Integrated Circuit Design.” 1999.
[BibTeX] [Link]

@inproceedings{61188758,
title = {A CurrentBased MOSFET Model for Integrated Circuit Design},
author = {{E. Sánchez-Sinencio} and {A. Andreou}},
year = 1999,
booktitle = {},
url = {https://www.semanticscholar.org/paper/b852e9c19e0488f2edaca7afd17a77d6aa9e1365},
}

T. Serrano-Gotarredona, A. Andreou, and B. Linares-Barranco, “A 2D image filtering architecture for real-time vision processing systems,” in Proceedings of the Seventh International Conference on Microelectronics for Neural, Fuzzy and Bio-Inspired Systems, 1999.
[BibTeX] [Link]

@inproceedings{62251046,
title = {A 2D image filtering architecture for real-time vision processing systems},
author = {{T. Serrano-Gotarredona} and {A. Andreou} and {B. Linares-Barranco}},
year = 1999,
month = {4},
booktitle = {Proceedings of the Seventh International Conference on Microelectronics for Neural, Fuzzy and Bio-Inspired Systems},
url = {https://www.semanticscholar.org/paper/d1e5d89a6540ae2e1d6f6070dd4c21708c205522},
}

E. Sánchez-Sinencio and A. Andreou, “LowVoltage Analog BiCMOS Circuit Building Blocks.” 1999.
[BibTeX] [Link]

@inproceedings{61252925,
title = {LowVoltage Analog BiCMOS Circuit Building Blocks},
author = {{E. Sánchez-Sinencio} and {A. Andreou}},
year = 1999,
booktitle = {},
url = {https://www.semanticscholar.org/paper/1c446c2ee21e6ec44d0873773c0961bb1b676a03},
}

E. Sánchez-Sinencio and A. Andreou, “Two New Directions in LowPower Digital CMOS VLSI Design.” 1999.
[BibTeX] [Link]

@inproceedings{59302418,
title = {Two New Directions in LowPower Digital CMOS VLSI Design},
author = {{E. Sánchez-Sinencio} and {A. Andreou}},
year = 1999,
booktitle = {},
url = {https://www.semanticscholar.org/paper/4a92a726eb7a19ed68d5403b9ed824d28e303883},
}

E. Sánchez-Sinencio and A. Andreou, “LowPower CMOS Digital Circuits.” 1999.
[BibTeX] [Link]

@inproceedings{61488609,
title = {LowPower CMOS Digital Circuits},
author = {{E. Sánchez-Sinencio} and {A. Andreou}},
year = 1999,
booktitle = {},
url = {https://www.semanticscholar.org/paper/eeac3a9131fabae5b6adb2d7a5ed25ed970023b4},
}

T. Serrano-Gotarredona, B. Linares-Barranco, and A. Andreou, “A general subthreshold MOS translinear theorem,” in ISCAS’99. Proceedings of the 1999 IEEE International Symposium on Circuits and Systems VLSI (Cat. No.99CH36349), 1999.
[BibTeX] [Link]

@inproceedings{36581757,
title = {A general subthreshold MOS translinear theorem},
author = {{T. Serrano-Gotarredona} and {B. Linares-Barranco} and {A. Andreou}},
year = 1999,
month = {5},
booktitle = {ISCAS'99. Proceedings of the 1999 IEEE International Symposium on Circuits and Systems VLSI (Cat. No.99CH36349)},
url = {https://www.semanticscholar.org/paper/d3bc768a9e44da258796884f67fbaac3418a5113},
}

P. Abshire and A. Andreou, “Relating information capacity to a biophysical model for blowfly retina,” in IJCNN’99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339), 1999.
[BibTeX] [Link]

@inproceedings{186405,
title = {Relating information capacity to a biophysical model for blowfly retina},
author = {{P. Abshire} and {A. Andreou}},
year = 1999,
month = {7},
booktitle = {IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339)},
url = {https://www.semanticscholar.org/paper/5f8360a147661199a0045a7dc76e4db44d4cdce6},
}

E. Sánchez-Sinencio and A. Andreou, “Micropower Systems for Implantable Defibrillators and Pacemakers.” 1999.
[BibTeX] [Link]

@inproceedings{74143354,
title = {Micropower Systems for Implantable Defibrillators and Pacemakers},
author = {{E. Sánchez-Sinencio} and {A. Andreou}},
year = 1999,
booktitle = {},
url = {https://www.semanticscholar.org/paper/c1dca39ea9ffb63fe0467b03604fc147dc29dce1},
}

Nagendra Kumar and A. Andreou, “Heteroscedastic discriminant analysis and reduced rank HMMs for improved speech recognition,” in Speech Communication, 1998.
[BibTeX] [Link]

@inproceedings{28539506,
title = {Heteroscedastic discriminant analysis and reduced rank HMMs for improved speech recognition},
author = {{Nagendra Kumar} and {A. Andreou}},
year = 1998,
month = {12},
booktitle = {Speech Communication},
url = {https://www.semanticscholar.org/paper/3fd4b226ecf0465d952fac3cc7d161a583a7c10c},
}

T. Serrano-Gotarredona, B. Linares-Barranco, and A. Andreou, “ART1 and ARTMAP VLSI Circuit Implementation.” 1998.
[BibTeX] [Link]

@inproceedings{62261210,
title = {ART1 and ARTMAP VLSI Circuit Implementation},
author = {{T. Serrano-Gotarredona} and {B. Linares-Barranco} and {A. Andreou}},
year = 1998,
booktitle = {},
url = {https://www.semanticscholar.org/paper/0ecc08d2532f8eabcd7defa2f3a3d623519ebfeb},
}

P. Hasler, A. Andreou, C. Diorio, B. Minch, and C. Mead, “Impact Ionization and Hot-Electron Injection Derived Consistently from Boltzmann Transport,” in VLSI design (Print), 1998.
[BibTeX] [Link]

@inproceedings{17291975,
title = {Impact Ionization and Hot-Electron Injection Derived Consistently from Boltzmann Transport},
author = {{P. Hasler} and {A. Andreou} and {C. Diorio} and {B. Minch} and {C. Mead}},
year = 1998,
booktitle = {VLSI design (Print)},
url = {https://www.semanticscholar.org/paper/ef96900a178f93b397d8a909ec585f09e8070d1c},
}

T. Serrano-Gotarredona, B. Linares-Barranco, and A. Andreou, “Analog Learning Fuzzy ART Chips.” 1998.
[BibTeX] [Link]

@inproceedings{108024869,
title = {Analog Learning Fuzzy ART Chips},
author = {{T. Serrano-Gotarredona} and {B. Linares-Barranco} and {A. Andreou}},
year = 1998,
booktitle = {},
url = {https://www.semanticscholar.org/paper/daaf3968e15e3c62c46a4cadc182169fcc40cf8d},
}

T. Serrano-Gotarredona, B. Linares-Barranco, and A. Andreou, “Voltage clamping current mirrors with 13-decades gain adjustment range suitable for low power MOS/bipolar current mode signal processing circuits,” in ISCAS ’98. Proceedings of the 1998 IEEE International Symposium on Circuits and Systems (Cat. No.98CH36187), 1998.
[BibTeX] [Link]

@inproceedings{58249601,
title = {Voltage clamping current mirrors with 13-decades gain adjustment range suitable for low power MOS/bipolar current mode signal processing circuits},
author = {{T. Serrano-Gotarredona} and {B. Linares-Barranco} and {A. Andreou}},
year = 1998,
month = {5},
booktitle = {ISCAS '98. Proceedings of the 1998 IEEE International Symposium on Circuits and Systems (Cat. No.98CH36187)},
url = {https://www.semanticscholar.org/paper/52200bc3603f73afc541eb32cd00dd5033f755ed},
}

T. Serrano-Gotarredona, B. Linares-Barranco, and A. Andreou, “Adaptive Resonance Theory Algorithms.” 1998.
[BibTeX] [Link]

@inproceedings{59915686,
title = {Adaptive Resonance Theory Algorithms},
author = {{T. Serrano-Gotarredona} and {B. Linares-Barranco} and {A. Andreou}},
year = 1998,
booktitle = {},
url = {https://www.semanticscholar.org/paper/a358defa85240dfa96355b668c430ccb990e189a},
}

T. Serrano-Gotarredona, B. Linares-Barranco, and A. Andreou, “Some Potential Applications For ART Microchips.” 1998.
[BibTeX] [Link]

@inproceedings{59708259,
title = {Some Potential Applications For ART Microchips},
author = {{T. Serrano-Gotarredona} and {B. Linares-Barranco} and {A. Andreou}},
year = 1998,
booktitle = {},
url = {https://www.semanticscholar.org/paper/89ff3049b4e1687f73cfb98e16e0f4b7256d7ac5},
}

T. Serrano-Gotarredona, B. Linares-Barranco, and A. Andreou, “An ART1/ARTMAP/Fuzzy-ART/Fuzzy-ARTMAP Chip.” 1998.
[BibTeX] [Link]

@inproceedings{59801958,
title = {An ART1/ARTMAP/Fuzzy-ART/Fuzzy-ARTMAP Chip},
author = {{T. Serrano-Gotarredona} and {B. Linares-Barranco} and {A. Andreou}},
year = 1998,
booktitle = {},
url = {https://www.semanticscholar.org/paper/61f9bda9b31d109fe219c0fd5bffaf0f12c1ce76},
}

T. Serrano-Gotarredona, B. Linares-Barranco, and A. Andreou, “A VLSI-Friendly ART1 Algorithm.” 1998.
[BibTeX] [Link]

@inproceedings{58801370,
title = {A VLSI-Friendly ART1 Algorithm},
author = {{T. Serrano-Gotarredona} and {B. Linares-Barranco} and {A. Andreou}},
year = 1998,
booktitle = {},
url = {https://www.semanticscholar.org/paper/fbd4fb462d699ad043d8cc9a4c723ae1b3c9564d},
}

T. Serrano-Gotarredona, B. Linares-Barranco, and A. Andreou, “MOS/bipolar active input current mirrors with 13–decades gain adjustment range,” in Proceedings of the 24th European Solid-State Circuits Conference, 1998.
[BibTeX] [Link]

@inproceedings{8970312,
title = {MOS/bipolar active input current mirrors with 13–decades gain adjustment range},
author = {{T. Serrano-Gotarredona} and {B. Linares-Barranco} and {A. Andreou}},
year = 1998,
booktitle = {Proceedings of the 24th European Solid-State Circuits Conference},
url = {https://www.semanticscholar.org/paper/364bea1db70b368ece8b17543bc582c543583851},
}

Z. Kalayjian and A. Andreou, “Integrated High Resolution Focal-Plane Polarization Imager.” 1998.
[BibTeX] [Link]

@inproceedings{17495926,
title = {Integrated High Resolution Focal-Plane Polarization Imager},
author = {{Z. Kalayjian} and {A. Andreou}},
year = 1998,
booktitle = {},
url = {https://www.semanticscholar.org/paper/fd35e758c56b85343fd8f68e96d7787c2f3078e7},
}

J. Eisner, “\sc FootForm Decomposed: Using Primitive Constraints in OT,” in Proceedings of SCIL VIII, Cambridge, MA, 1998, p. 115–143.
[BibTeX] [Link]

@InProceedings{eisner-1997-scil,
author = "Jason Eisner",
title = "{\sc FootForm} Decomposed: Using Primitive Constraints
in {OT}",
booktitle = "Proceedings of SCIL VIII",
series = "MIT Working Papers in Linguistics",
number = "31",
pages = "115--143",
editor = "Benjamin Bruening",
year = "1998",
address = "Cambridge, MA",
URL = "http://cs.jhu.edu/~jason/papers/#eisner-1997-scil",
}

J. Eisner, “Bilexical Grammars and a Cubic-Time Probabilistic Parser,” in Proceedings of the 5th International Workshop on Parsing Technologies (IWPT), MIT, Cambridge, MA, 1997, p. 54–65.
[BibTeX] [Link]

@InProceedings{eisner-1997-iwpt,
author = "Jason Eisner",
title = "Bilexical Grammars and a Cubic-Time Probabilistic
Parser",
booktitle = "Proceedings of the 5th International Workshop on
Parsing Technologies (IWPT)",
pages = "54--65",
year = "1997",
month = sep,
address = "MIT, Cambridge, MA",
URL = "http://cs.jhu.edu/~jason/papers/#eisner-1997-iwpt",
}

J. Eisner, “Efficient Generation in Primitive Optimality Theory,” in Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics (ACL), Madrid, 1997, p. 313–320.
[BibTeX] [Link]

@InProceedings{eisner-1997-acl,
aclid = "P97-1040",
author = "Jason Eisner",
title = "Efficient Generation in Primitive {O}ptimality
{T}heory",
booktitle = "Proceedings of the 35th Annual Meeting of the
Association for Computational Linguistics (ACL)",
pages = "313--320",
year = "1997",
month = jul,
address = "Madrid",
URL = "http://cs.jhu.edu/~jason/papers/#eisner-1997-acl",
}

Nagendra Kumar, W. Himmelbauer, G. Cauwenberghs, and A. Andreou, “An analog VLSI architecture for auditory based feature extraction,” in IEEE International Conference on Acoustics, Speech, and Signal Processing, 1997.
[BibTeX] [Link]

@inproceedings{681336,
title = {An analog VLSI architecture for auditory based feature extraction},
author = {{Nagendra Kumar} and {W. Himmelbauer} and {G. Cauwenberghs} and {A. Andreou}},
year = 1997,
month = {4},
booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
url = {https://www.semanticscholar.org/paper/ba63dbbe9f16fd6d8ec1e56f8af524e44aa64b61},
}

Z. Kalayjian and A. Andreou, “Asynchronous Communication of 2D Motion Information Using Winner-Takes-All Arbitration,” in Analog Integrated Circuits and Signal Processing, 1997.
[BibTeX] [Link]

@inproceedings{56915443,
title = {Asynchronous Communication of 2D Motion Information Using Winner-Takes-All Arbitration},
author = {{Z. Kalayjian} and {A. Andreou}},
year = 1997,
month = {5},
booktitle = {Analog Integrated Circuits and Signal Processing},
url = {https://www.semanticscholar.org/paper/57831a73adb42bcfc25542965c77f1f17749ce05},
}

N. Kumar, W. Himmelbauer, G. Cauwenberghs, and A. Andreou, “An analog VLSI front-end for auditory signal analysis,” in International Conference on Neural Networks, 1997.
[BibTeX] [Link]

@inproceedings{61931137,
title = {An analog VLSI front-end for auditory signal analysis},
author = {{N. Kumar} and {W. Himmelbauer} and {G. Cauwenberghs} and {A. Andreou}},
year = 1997,
month = {6},
booktitle = {International Conference on Neural Networks},
url = {https://www.semanticscholar.org/paper/7a791e3a7e1491f69c884172a39528920cd9fd28},
}

P. Furth and A. Andreou, “On fault probabilities and yield models for VLSI neural networks,” in IEEE J. Solid State Circuits, 1997.
[BibTeX] [Link]

@inproceedings{17770135,
title = {On fault probabilities and yield models for VLSI neural networks},
author = {{P. Furth} and {A. Andreou}},
year = 1997,
month = {8},
booktitle = {IEEE J. Solid State Circuits},
url = {https://www.semanticscholar.org/paper/653c2e248ee2f23b49f5d1d40398c69173ab7be0},
}

A. Obeidat, Z. Kalayjian, A. Andreou, and J. Khurgin, “A model for visible photon emission from reverse-biased silicon p-n junctions,” in Applied Physics Letters, 1997.
[BibTeX] [Link]

@inproceedings{123193697,
title = {A model for visible photon emission from reverse-biased silicon p-n junctions},
author = {{A. Obeidat} and {Z. Kalayjian} and {A. Andreou} and {J. Khurgin}},
year = 1997,
month = {1},
booktitle = {Applied Physics Letters},
url = {https://www.semanticscholar.org/paper/b3ab53c5eaeb09d962bb102483b61a1950639f8a},
}

N. Kumar, G. Cauwenberghs, and A. Andreou, “Auditory feature extraction using self-timed, continuous-time discrete-signal processing circuits,” in IEEE Transactions on Circuits and Systems Ii: Analog and Digital Signal Processing, 1997.
[BibTeX] [Link]

@inproceedings{10372060,
title = {Auditory feature extraction using self-timed, continuous-time discrete-signal processing circuits},
author = {{N. Kumar} and {G. Cauwenberghs} and {A. Andreou}},
year = 1997,
month = {9},
booktitle = {IEEE Transactions on Circuits and Systems Ii: Analog and Digital Signal Processing},
url = {https://www.semanticscholar.org/paper/de3a95bde46e390c7c141ee6113222bff39351ea},
}

N. Kumar, W. Himmelbauer, Gert Cauwenberghs, and A. Andreou, “An analog VLSI chip with asynchronous interface for auditory feature extraction,” in Proceedings of 1997 IEEE International Symposium on Circuits and Systems. Circuits and Systems in the Information Age ISCAS ’97, 1997.
[BibTeX] [Link]

@inproceedings{16138143,
title = {An analog VLSI chip with asynchronous interface for auditory feature extraction},
author = {{N. Kumar} and {W. Himmelbauer} and {Gert Cauwenberghs} and {A. Andreou}},
year = 1997,
month = {6},
booktitle = {Proceedings of 1997 IEEE International Symposium on Circuits and Systems. Circuits and Systems in the Information Age ISCAS '97},
url = {https://www.semanticscholar.org/paper/c5cd5019321623a0b01399efedd50282cd337d68},
}

A. Andreou and N. Kumar, “Investigation of silicon auditory models and generalization of linear discriminant analysis for improved speech recognition.” 1997.
[BibTeX] [Link]

@inproceedings{61052539,
title = {Investigation of silicon auditory models and generalization of linear discriminant analysis for improved speech recognition},
author = {{A. Andreou} and {N. Kumar}},
year = 1997,
booktitle = {},
url = {https://www.semanticscholar.org/paper/d7f5f913fcb96d8c351a36d4b1cf5833f7880691},
}

P. Pouliquen, A. Andreou, and K. Strohbehn, “Winner-Takes-All Associative Memory: A Hamming Distance Vector Quantizer,” in Analog Integrated Circuits and Signal Processing, 1997.
[BibTeX] [Link]

@inproceedings{61004814,
title = {Winner-Takes-All Associative Memory: A Hamming Distance Vector Quantizer},
author = {{P. Pouliquen} and {A. Andreou} and {K. Strohbehn}},
year = 1997,
month = {5},
booktitle = {Analog Integrated Circuits and Signal Processing},
url = {https://www.semanticscholar.org/paper/3a59a5c9a44fc98db8d789b0a057c239c5a8834f},
}

J. Eisner, “Three New Probabilistic Models for Dependency Parsing: An Exploration,” in Proceedings of the 16th International Conference on Computational Linguistics (COLING-96), Copenhagen, 1996, p. 340–345.
[BibTeX] [Link]

@InProceedings{eisner-1996-coling,
aclid = "C96-1058",
author = "Jason Eisner",
title = "Three New Probabilistic Models for Dependency Parsing:
An Exploration",
booktitle = "Proceedings of the 16th International Conference on
Computational Linguistics (COLING-96)",
pages = "340--345",
year = "1996",
month = aug,
address = "Copenhagen",
URL = "http://cs.jhu.edu/~jason/papers/#eisner-1996-coling",
}

J. Eisner, “Efficient Normal-Form Parsing for Combinatory Categorial Grammar,” in Proceedings of the 34th Annual Meeting of the Association for Computational Linguistics (ACL), Santa Cruz, 1996, p. 79–86.
[BibTeX] [Link]

@InProceedings{eisner-1996-acl,
aclid = "P96-1011",
author = "Jason Eisner",
title = "Efficient Normal-Form Parsing for Combinatory
Categorial Grammar",
booktitle = "Proceedings of the 34th Annual Meeting of the
Association for Computational Linguistics (ACL)",
pages = "79--86",
year = "1996",
month = jun,
address = "Santa Cruz",
URL = "http://cs.jhu.edu/~jason/papers/#eisner-1996-acl",
}

Z. Kalayjian, A. Andreou, L. Wolff, and Norman Sheppard, “A Polarization Contrast Retina That Uses Patterned Iodine-Doped PVA Film.” 1996.
[BibTeX] [Link]

@inproceedings{17673412,
title = {A Polarization Contrast Retina That Uses Patterned Iodine-Doped PVA Film},
author = {{Z. Kalayjian} and {A. Andreou} and {L. Wolff} and {Norman Sheppard}},
year = 1996,
booktitle = {},
url = {https://www.semanticscholar.org/paper/46756dd3cc254c772b212678d3b65acecec36148},
}

R. C. Meitzler and A. Andreou, “Modeling nonuniform doping in subthreshold MOSFETs,” in Proceedings of the 39th Midwest Symposium on Circuits and Systems, 1996.
[BibTeX] [Link]

@inproceedings{56842686,
title = {Modeling nonuniform doping in subthreshold MOSFETs},
author = {{R. C. Meitzler} and {A. Andreou}},
year = 1996,
month = {8},
booktitle = {Proceedings of the 39th Midwest Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/da80aa60b81a75e26d17c6d1855afd28d1b90799},
}

N. Kumar and A. Andreou, “On Generalizations of Linear Discriminant Analysis.” 1996.
[BibTeX] [Link]

@inproceedings{16081514,
title = {On Generalizations of Linear Discriminant Analysis},
author = {{N. Kumar} and {A. Andreou}},
year = 1996,
booktitle = {},
url = {https://www.semanticscholar.org/paper/db2605efc076059d07b6a7484e7ad247054b6ea7},
}

Z. Kalayjian, J. Waskiewicz, D. Yochelson, and A. Andreou, “Asynchronous sampling of 2D arrays using winner-takes-all arbitration,” in 1996 IEEE International Symposium on Circuits and Systems. Circuits and Systems Connecting the World. ISCAS 96, 1996.
[BibTeX] [Link]

@inproceedings{62313979,
title = {Asynchronous sampling of 2D arrays using winner-takes-all arbitration},
author = {{Z. Kalayjian} and {J. Waskiewicz} and {D. Yochelson} and {A. Andreou}},
year = 1996,
month = {5},
booktitle = {1996 IEEE International Symposium on Circuits and Systems. Circuits and Systems Connecting the World. ISCAS 96},
url = {https://www.semanticscholar.org/paper/d45acfe1547afd403023008e6eb43822a7201235},
}

M.N. Martin, P. Pouliquen, A. Andreou, and M.E. Fraeman, “Current-mode differential logic circuits for low power digital systems,” in Proceedings of the 39th Midwest Symposium on Circuits and Systems, 1996.
[BibTeX] [Link]

@inproceedings{108433087,
title = {Current-mode differential logic circuits for low power digital systems},
author = {{M.N. Martin} and {P. Pouliquen} and {A. Andreou} and {M.E. Fraeman}},
year = 1996,
month = {8},
booktitle = {Proceedings of the 39th Midwest Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/2800ed5c41d8bd76719344c05304c1b5991c6c3b},
}

Z. Kalayjian, A. Andreou, L. Wolff, and Norman Sheppard, “A Polarization Contrast Retina Using Patterned Iodine-doped PVA Film,” in European Solid-State Circuits Conference, 1996.
[BibTeX] [Link]

@inproceedings{26235255,
title = {A Polarization Contrast Retina Using Patterned Iodine-doped PVA Film},
author = {{Z. Kalayjian} and {A. Andreou} and {L. Wolff} and {Norman Sheppard}},
year = 1996,
month = {9},
booktitle = {European Solid-State Circuits Conference},
url = {https://www.semanticscholar.org/paper/8ba80257f2e9573a83d85e4b4128a3b5a0f44c84},
}

N. Kumar, G. Cauwenberghs, and A. Andreou, “A circuit model of hair-cell transduction for temporal processing and auditory feature extraction,” in 1996 IEEE International Symposium on Circuits and Systems. Circuits and Systems Connecting the World. ISCAS 96, 1996.
[BibTeX] [Link]

@inproceedings{62657012,
title = {A circuit model of hair-cell transduction for temporal processing and auditory feature extraction},
author = {{N. Kumar} and {G. Cauwenberghs} and {A. Andreou}},
year = 1996,
month = {5},
booktitle = {1996 IEEE International Symposium on Circuits and Systems. Circuits and Systems Connecting the World. ISCAS 96},
url = {https://www.semanticscholar.org/paper/ea12c40b0ed6fcbb9d8e116df16bb0f5ba4ce624},
}

P. Furth and A. Andreou, “Translinear transconductor design for cochlear filter banks,” in Proceedings of the 39th Midwest Symposium on Circuits and Systems, 1996.
[BibTeX] [Link]

@inproceedings{15900907,
title = {Translinear transconductor design for cochlear filter banks},
author = {{P. Furth} and {A. Andreou}},
year = 1996,
month = {8},
booktitle = {Proceedings of the 39th Midwest Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/598c6d9959085d8faf2dda342443fc11e64b2ffd},
}

A. Andreou and K. Boahen, “Translinear circuits in subthreshold MOS,” in Analog Integrated Circuits and Signal Processing, 1996.
[BibTeX] [Link]

@inproceedings{62169532,
title = {Translinear circuits in subthreshold MOS},
author = {{A. Andreou} and {K. Boahen}},
year = 1996,
month = {3},
booktitle = {Analog Integrated Circuits and Signal Processing},
url = {https://www.semanticscholar.org/paper/c0b254eec92da2c17b53dd05060e92f7d8f7a14e},
}

FRAMEWORKNagendra, Kumar, A. Andreou, Johns Hopkins, UniversityNagendra, B. Hall, and N. C. St, “A GENERALIZATION OF LINEAR DISCRIMINANT ANALYSIS INMAXIMUM LIKELIHOOD.” 1996.
[BibTeX] [Link]

@inproceedings{6568086,
title = {A GENERALIZATION OF LINEAR DISCRIMINANT ANALYSIS INMAXIMUM LIKELIHOOD},
author = {{FRAMEWORKNagendra} and {Kumar} and {A. Andreou} and {Johns Hopkins} and {UniversityNagendra} and {B. Hall} and {N. C. St}},
year = 1996,
booktitle = {},
url = {https://www.semanticscholar.org/paper/553cf797ae70839b28afce91e86ab6f50b4e01e3},
}

A. Andreou and K. Boahen, “Analog Integrated Circuits and Signal Processing,” in Analog Integrated Circuits and Signal Processing, 1996.
[BibTeX] [Link]

@inproceedings{16993216,
title = {Analog Integrated Circuits and Signal Processing},
author = {{A. Andreou} and {K. Boahen}},
year = 1996,
booktitle = {Analog Integrated Circuits and Signal Processing},
url = {https://www.semanticscholar.org/paper/4c756a4824b0b605b021c5f4fa4d716857c362a1},
}

A. Andreou, R. C. Meitzler, K. Strohbehn, and K. Boahen, “Analog VLSI neuromorphic image acquisition and pre-processing systems,” in Neural Networks, 1995.
[BibTeX] [Link]

@inproceedings{29109920,
title = {Analog VLSI neuromorphic image acquisition and pre-processing systems},
author = {{A. Andreou} and {R. C. Meitzler} and {K. Strohbehn} and {K. Boahen}},
year = 1995,
month = {12},
booktitle = {Neural Networks},
url = {https://www.semanticscholar.org/paper/e114041a1e42fe305ceb050d8a372073c3766d80},
}

P. Furth and A. Andreou, “A design framework for low power analog filter banks,” in IEEE Transactions on Circuits and Systems I-regular Papers, 1995.
[BibTeX] [Link]

@inproceedings{18736374,
title = {A design framework for low power analog filter banks},
author = {{P. Furth} and {A. Andreou}},
year = 1995,
month = {11},
booktitle = {IEEE Transactions on Circuits and Systems I-regular Papers},
url = {https://www.semanticscholar.org/paper/82b451ba770771fff2ad318f017540f78b15e6f5},
}

B. Baldwin, J. Reynar, M. Collins, J. Eisner, A. Ratnaparkhi, Joseph Rosenzweig, A. Sarkar, and Srinivas, “Description of the University of Pennsylvania Entry in the MUC-6 Competition,” in Proceedings of the Sixth Message Understanding Conference, Maryland, 1995, p. 177–191.
[BibTeX] [Link]

@InProceedings{baldwin-et-al-1995,
aclid = "M95-1015",
author = "Breck Baldwin and Jeff Reynar and Mike Collins and
Jason Eisner and Adwait Ratnaparkhi and Joseph
Rosenzweig and Anoop Sarkar and Srinivas",
title = "Description of the {U}niversity of {P}ennsylvania
Entry in the {MUC}-6 Competition",
booktitle = "Proceedings of the Sixth Message Understanding
Conference",
pages = "177--191",
year = "1995",
month = oct,
address = "Maryland",
URL = "http://cs.jhu.edu/~jason/papers/#baldwin-et-al-1995",
}

A. Andreou, “Book Review: “Cellular Neural Networks”, by T. Roska and J. Vandewalle,” in International Journal of Neural Systems, 1995.
[BibTeX] [Link]

@inproceedings{39415148,
title = {Book Review: "Cellular Neural Networks", by T. Roska and J. Vandewalle},
author = {{A. Andreou}},
year = 1995,
month = {6},
booktitle = {International Journal of Neural Systems},
url = {https://www.semanticscholar.org/paper/67c8ee8ca7f3ef8eba7e0c15dcece598e9e43e03},
}

L. B. Wolff and A. Andreou, “Polarization camera sensors,” in Image and Vision Computing, 1995.
[BibTeX] [Link]

@inproceedings{11362831,
title = {Polarization camera sensors},
author = {{L. B. Wolff} and {A. Andreou}},
year = 1995,
month = {8},
booktitle = {Image and Vision Computing},
url = {https://www.semanticscholar.org/paper/df7df9009491654012075c869e309ef2efef4127},
}

Jordan Cohen, T. Kamm, and A. Andreou, “Vocal tract normalization in speech recognition: Compensating for systematic speaker variability,” in Journal of the Acoustical Society of America, 1995.
[BibTeX] [Link]

@inproceedings{120356311,
title = {Vocal tract normalization in speech recognition: Compensating for systematic speaker variability},
author = {{Jordan Cohen} and {T. Kamm} and {A. Andreou}},
year = 1995,
month = {5},
booktitle = {Journal of the Acoustical Society of America},
url = {https://www.semanticscholar.org/paper/b32cf0f63de63b339a0ed24a5b8788f8cbe86827},
}

R. C. Meitzler, K. Strohbehn, and A. Andreou, “A silicon retina for 2-D position and motion computation,” in International Symposium on Circuits and Systems, 1995.
[BibTeX] [Link]

@inproceedings{59161903,
title = {A silicon retina for 2-D position and motion computation},
author = {{R. C. Meitzler} and {K. Strohbehn} and {A. Andreou}},
year = 1995,
month = {4},
booktitle = {International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/f7b2f5ec2182dc260e3ae826f3a37e1ae82602f9},
}

P. Furth and A. Andreou, “Linearised differential transconductors in subthreshold CMOS,” in Electronics Letters, 1995.
[BibTeX] [Link]

@inproceedings{18903153,
title = {Linearised differential transconductors in subthreshold CMOS},
author = {{P. Furth} and {A. Andreou}},
year = 1995,
month = {3},
booktitle = {Electronics Letters},
url = {https://www.semanticscholar.org/paper/47d4f6710d52d4864a7a5ff7b8e4d91ada7f6923},
}

N. Kumar, C. Neti, and A. Andreou, “Application of Discriminant Analysis to Speech Recognition with Auditory Features.” 1995.
[BibTeX] [Link]

@inproceedings{16849251,
title = {Application of Discriminant Analysis to Speech Recognition with Auditory Features},
author = {{N. Kumar} and {C. Neti} and {A. Andreou}},
year = 1995,
booktitle = {},
url = {https://www.semanticscholar.org/paper/99db8a4f8c13a4b9cb4336b556c87e9cf9d3cb50},
}

A. Andreou and K. Boahen, “A 590,000 transistor 48,000 pixel, contrast sensitive, edge enhancing, CMOS imager-silicon retina,” in Proceedings Sixteenth Conference on Advanced Research in VLSI, 1995.
[BibTeX] [Link]

@inproceedings{6791864,
title = {A 590,000 transistor 48,000 pixel, contrast sensitive, edge enhancing, CMOS imager-silicon retina},
author = {{A. Andreou} and {K. Boahen}},
year = 1995,
month = {3},
booktitle = {Proceedings Sixteenth Conference on Advanced Research in VLSI},
url = {https://www.semanticscholar.org/paper/ddd0f73681f6c08f081577056b05ef783f1792d8},
}

M. Cohen and A. Andreou, “Analog CMOS integration and experimentation with an autoadaptive independent component analyzer.” 1995.
[BibTeX] [Link]

@inproceedings{60858644,
title = {Analog CMOS integration and experimentation with an autoadaptive independent component analyzer},
author = {{M. Cohen} and {A. Andreou}},
year = 1995,
month = {2},
booktitle = {},
url = {https://www.semanticscholar.org/paper/1483ad8f59ebd5f7cf4f97f859a50b544b842078},
}

N. Kumar, G. Cauwenberghs, and A. Andreou, “Level crossing time interval circuit for micro-power analog VLSI auditory processing,” in Proceedings of 1995 IEEE Workshop on Neural Networks for Signal Processing, 1995.
[BibTeX] [Link]

@inproceedings{63990645,
title = {Level crossing time interval circuit for micro-power analog VLSI auditory processing},
author = {{N. Kumar} and {G. Cauwenberghs} and {A. Andreou}},
year = 1995,
month = {8},
booktitle = {Proceedings of 1995 IEEE Workshop on Neural Networks for Signal Processing},
url = {https://www.semanticscholar.org/paper/7dd477a54aaf4110b504ad1e76eed4b045f7aed5},
}

R. C. Meitzler, K. Strohbehn, and A. Andreou, “A Silicon Retina for 2-D Position and 2-D Motion Computation,” in International Symposium on Circuits and Systems, 1995.
[BibTeX] [Link]

@inproceedings{702299,
title = {A Silicon Retina for 2-D Position and 2-D Motion Computation},
author = {{R. C. Meitzler} and {K. Strohbehn} and {A. Andreou}},
year = 1995,
booktitle = {International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/ce43cbad87d2327b136f643a4e6b5cc15b8939eb},
}

P. Furth and A. Andreou, “Transconductors in Subthreshold CMOS.” 1995.
[BibTeX] [Link]

@inproceedings{10065245,
title = {Transconductors in Subthreshold CMOS},
author = {{P. Furth} and {A. Andreou}},
year = 1995,
booktitle = {},
url = {https://www.semanticscholar.org/paper/f75689e3827e1901153d2d65c083f4b10ad8035e},
}

J. Eisner, “$\forall$-less in Wonderland? Revisiting \em any,” in Proceedings of ESCOL 11 (October 1994), Ithaca, NY, 1995, p. 92–103.
[BibTeX] [Link]

@InProceedings{eisner-1995,
author = "Jason Eisner",
title = "{$\forall$}-less in {W}onderland? {R}evisiting {\em
any}",
booktitle = "Proceedings of ESCOL 11 (October 1994)",
pages = "92--103",
year = "1995",
editor = "Janet Fuller and Ho Han and David Parkinson",
address = "Ithaca, NY",
publisher = "DMLL Publications",
URL = "http://cs.jhu.edu/~jason/papers/#eisner-1995",
}

A. Andreou, “On physical models of neural computation and their analog VLSI implementation,” in Proceedings Workshop on Physics and Computation. PhysComp ’94, 1994.
[BibTeX] [Link]

@inproceedings{61603974,
title = {On physical models of neural computation and their analog VLSI implementation},
author = {{A. Andreou}},
year = 1994,
month = {11},
booktitle = {Proceedings Workshop on Physics and Computation. PhysComp '94},
url = {https://www.semanticscholar.org/paper/99f36b2afc82c8aa67647f1cba9139d823141508},
}

Kewei Yang and A. Andreou, “A multiple input differential amplifier based on charge sharing on a floating-gate MOSFET,” in Analog Integrated Circuits and Signal Processing, 1994.
[BibTeX] [Link]

@inproceedings{60906457,
title = {A multiple input differential amplifier based on charge sharing on a floating-gate MOSFET},
author = {{Kewei Yang} and {A. Andreou}},
year = 1994,
month = {11},
booktitle = {Analog Integrated Circuits and Signal Processing},
url = {https://www.semanticscholar.org/paper/adae53898fcd2fa4cacd560feab4de72e24da9a5},
}

F. Pineda and A. Andreou, “ANALOG NEUROMORPHIC COMPUTATION: AN APPLICATION TO COMPRESSION.” 1994.
[BibTeX] [Link]

@inproceedings{1371034,
title = {ANALOG NEUROMORPHIC COMPUTATION: AN APPLICATION TO COMPRESSION},
author = {{F. Pineda} and {A. Andreou}},
year = 1994,
booktitle = {},
url = {https://www.semanticscholar.org/paper/f3d1bcf2698bb24b90e8b790f4cb1e48aa7d5d9e},
}

V. Kantabutra and A. Andreou, “A State Assignment Approach to Asynchronous CMOS Circuit Design,” in IEEE Trans. Computers, 1994.
[BibTeX] [Link]

@inproceedings{7235015,
title = {A State Assignment Approach to Asynchronous CMOS Circuit Design},
author = {{V. Kantabutra} and {A. Andreou}},
year = 1994,
month = {4},
booktitle = {IEEE Trans. Computers},
url = {https://www.semanticscholar.org/paper/fdce6dff1bcad588391f08e6097a3d4c0653c907},
}

V. Kantabutra and A. Andreou, “A State Assignment Approach to Asynchronous.” 1994.
[BibTeX] [Link]

@inproceedings{62261327,
title = {A State Assignment Approach to Asynchronous},
author = {{V. Kantabutra} and {A. Andreou}},
year = 1994,
booktitle = {},
url = {https://www.semanticscholar.org/paper/7cc8b60de98e319109120df599c62ff0217b5bd6},
}

Kewei Yang and A. Andreou, “The multiple input floating gate MOS differential amplifier: an analog computational building-block,” in International Symposium on Circuits and Systems, 1994.
[BibTeX] [Link]

@inproceedings{40552257,
title = {The multiple input floating gate MOS differential amplifier: an analog computational building-block},
author = {{Kewei Yang} and {A. Andreou}},
year = 1994,
month = {5},
booktitle = {International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/9d6c3340c013774534b96aa1b7c9e274b137060e},
}

A. Pavasovic, A. Andreou, and C. Westgate, “Characterization of subthreshold MOS mismatch in transistors for VLSI systems,” in Analog Integrated Circuits and Signal Processing, 1994.
[BibTeX] [Link]

@inproceedings{62242197,
title = {Characterization of subthreshold MOS mismatch in transistors for VLSI systems},
author = {{A. Pavasovic} and {A. Andreou} and {C. Westgate}},
year = 1994,
month = {7},
booktitle = {Analog Integrated Circuits and Signal Processing},
url = {https://www.semanticscholar.org/paper/09644bd9d093ecb64d3ad0026c953efd3300a87d},
}

H. Miwa, Kewei Yang, P. Pouliquen, Nagendra Kumar, and A. Andreou, “Storage enhancement techniques for digital memory based, analog computational engines,” in International Symposium on Circuits and Systems, 1994.
[BibTeX] [Link]

@inproceedings{20077335,
title = {Storage enhancement techniques for digital memory based, analog computational engines},
author = {{H. Miwa} and {Kewei Yang} and {P. Pouliquen} and {Nagendra Kumar} and {A. Andreou}},
year = 1994,
month = {5},
booktitle = {International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/754447bd13cbf3819163211f14e3fa4dca4ff850},
}

V. Kantabutra and A. Andreou, “Approach to Asynchronous Circuit Design.” 1994.
[BibTeX] [Link]

@inproceedings{62948433,
title = {Approach to Asynchronous Circuit Design},
author = {{V. Kantabutra} and {A. Andreou}},
year = 1994,
booktitle = {},
url = {https://www.semanticscholar.org/paper/ca22db4a450c6832f63a1987fd960deea87979ef},
}

P. Furth, N. Goel, A. Andreou, and M. Goldstein, “Experiments with the Hopkins Electronic EAR.” 1994.
[BibTeX] [Link]

@inproceedings{17321155,
title = {Experiments with the Hopkins Electronic EAR},
author = {{P. Furth} and {N. Goel} and {A. Andreou} and {M. Goldstein}},
year = 1994,
booktitle = {},
url = {https://www.semanticscholar.org/paper/b22b8ff72e1533baf00d444535abd13a88950b32},
}

A. Andreou and T. Edwards, “Analog VLSI neuromorphic processing: case study of a multiple-target-tracking system,” in International Conference on Neural Networks, 1994.
[BibTeX] [Link]

@inproceedings{60712536,
title = {Analog VLSI neuromorphic processing: case study of a multiple-target-tracking system},
author = {{A. Andreou} and {T. Edwards}},
year = 1994,
month = {6},
booktitle = {International Conference on Neural Networks},
url = {https://www.semanticscholar.org/paper/31d62a1fe435c188a80f08c819684e131b321be0},
}

A. Andreou and K. Boahen, “A 48,000 pixel, 590,000 transistor silicon retina in current-mode subthreshold CMOS,” in Proceedings of 1994 37th Midwest Symposium on Circuits and Systems, 1994.
[BibTeX] [Link]

@inproceedings{60882320,
title = {A 48,000 pixel, 590,000 transistor silicon retina in current-mode subthreshold CMOS},
author = {{A. Andreou} and {K. Boahen}},
year = 1994,
month = {8},
booktitle = {Proceedings of 1994 37th Midwest Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/bcae76b0358316e78160918962ae3c5b7f7d70d0},
}

A. Murray, I. Aleksander, A. Andreou, and M. Mahowald, “Analogue and Digital Neural VLSI: Duet or Duel?,” in International Symposium on Circuits and Systems, 1994.
[BibTeX] [Link]

@inproceedings{41409703,
title = {Analogue and Digital Neural VLSI: Duet or Duel?},
author = {{A. Murray} and {I. Aleksander} and {A. Andreou} and {M. Mahowald}},
year = 1994,
booktitle = {International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/7a9eed09e013a7c5b54d1382a7dfab72f7cb068b},
}

F. Pineda and A. Andreou, “An Analog Neural Network Inspired by Fractal Block Coding,” in Neural Information Processing Systems, 1994.
[BibTeX] [Link]

@inproceedings{5788151,
title = {An Analog Neural Network Inspired by Fractal Block Coding},
author = {{F. Pineda} and {A. Andreou}},
year = 1994,
booktitle = {Neural Information Processing Systems},
url = {https://www.semanticscholar.org/paper/072444b064842560a91f06e06157d9812a2c6c9a},
}

A. Pavasovic, A. Andreou, and C. Westgate, “Characterization of subthreshold MOS mismatch in transistors for VLSI systems,” in J. VLSI Signal Process., 1994.
[BibTeX] [Link]

@inproceedings{31862699,
title = {Characterization of subthreshold MOS mismatch in transistors for VLSI systems},
author = {{A. Pavasovic} and {A. Andreou} and {C. Westgate}},
year = 1994,
booktitle = {J. VLSI Signal Process.},
url = {https://www.semanticscholar.org/paper/471dd4a784a2c07ab31172741081bd8e895d30ac},
}

Kewei Yang, R. C. Meitzler, and A. Andreou, “A model for MOS effective channel mobility with emphasis in the subthreshold and transition region,” in International Symposium on Circuits and Systems, 1994.
[BibTeX] [Link]

@inproceedings{26284191,
title = {A model for MOS effective channel mobility with emphasis in the subthreshold and transition region},
author = {{Kewei Yang} and {R. C. Meitzler} and {A. Andreou}},
year = 1994,
month = {5},
booktitle = {International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/81f137f92bf5763516657b1a0667801947c75870},
}

K. Strohbehm, David Rust, A. Andreou, and R. E. Jenkins, “A Biologically-Inspired Image Position Sensor.” 1993.
[BibTeX] [Link]

@inproceedings{117220967,
title = {A Biologically-Inspired Image Position Sensor},
author = {{K. Strohbehm} and {David Rust} and {A. Andreou} and {R. E. Jenkins}},
year = 1993,
month = {12},
booktitle = {},
url = {https://www.semanticscholar.org/paper/06879508b31d1f7eec29b3d9b4499de273c5f991},
}

A. Andreou and T. Edwards, “VLSI Phase Locking Architectures for Feature Linking in Multiple Target Tracking Systems,” in Neural Information Processing Systems, 1993.
[BibTeX] [Link]

@inproceedings{14436183,
title = {VLSI Phase Locking Architectures for Feature Linking in Multiple Target Tracking Systems},
author = {{A. Andreou} and {T. Edwards}},
year = 1993,
month = {11},
booktitle = {Neural Information Processing Systems},
url = {https://www.semanticscholar.org/paper/d90b8d0d100f1903d97f5ab58a75a6e093e3f192},
}

N. Paschalidis, A. Andreou, E. Sarris, and S. Krimigis, “Application Specific Integrated Circuits (ASICs) for Particle Measurements in Space Using Solid State Detectors.” 1993.
[BibTeX] [Link]

@inproceedings{107779550,
title = {Application Specific Integrated Circuits (ASICs) for Particle Measurements in Space Using Solid State Detectors},
author = {{N. Paschalidis} and {A. Andreou} and {E. Sarris} and {S. Krimigis}},
year = 1993,
month = {11},
booktitle = {},
url = {https://www.semanticscholar.org/paper/b07876c0240b87c8ddaa094b134d4acf3787b56b},
}

N. Paschalidis, A. Andreou, and E. Sarris, “A CMOS analog-digital integrated circuit for charged particle spectrum measurements,” in IEEE Transactions on Nuclear Science, 1993.
[BibTeX] [Link]

@inproceedings{53286050,
title = {A CMOS analog-digital integrated circuit for charged particle spectrum measurements},
author = {{N. Paschalidis} and {A. Andreou} and {E. Sarris}},
year = 1993,
booktitle = {IEEE Transactions on Nuclear Science},
url = {https://www.semanticscholar.org/paper/2a815fa1111b36651908f6da3d037715b0d121fe},
}

K. Yang and A. Andreou, “Subthreshold analysis of floating-gate MOSFET’s,” in [1993] Proceedings of the Tenth Biennial University/Government/Industry Microelectronics Symposium, 1993.
[BibTeX] [Link]

@inproceedings{110032741,
title = {Subthreshold analysis of floating-gate MOSFET's},
author = {{K. Yang} and {A. Andreou}},
year = 1993,
month = {5},
booktitle = {[1993] Proceedings of the Tenth Biennial University/Government/Industry Microelectronics Symposium},
url = {https://www.semanticscholar.org/paper/2207ad1cd67668a7a79a52f03d2e8cac0bd289e3},
}

K. Strohbehn, R. E. Jenkins, X. Sun, and A. Andreou, “Silicon retina for optical tracking systems.” 1993.
[BibTeX] [Link]

@inproceedings{109568542,
title = {Silicon retina for optical tracking systems},
author = {{K. Strohbehn} and {R. E. Jenkins} and {X. Sun} and {A. Andreou}},
year = 1993,
booktitle = {},
url = {https://www.semanticscholar.org/paper/7f414c46e2bd7b886370826940b7057708604627},
}

R. C. Meitzler and A. Andreou, “On the simulation of analog VLSI systems operating in the subthreshold and transition regions,” in [1993] Proceedings of the Tenth Biennial University/Government/Industry Microelectronics Symposium, 1993.
[BibTeX] [Link]

@inproceedings{109401790,
title = {On the simulation of analog VLSI systems operating in the subthreshold and transition regions},
author = {{R. C. Meitzler} and {A. Andreou}},
year = 1993,
month = {5},
booktitle = {[1993] Proceedings of the Tenth Biennial University/Government/Industry Microelectronics Symposium},
url = {https://www.semanticscholar.org/paper/c894aeec7bb30084cc9d6e2de07be3884f379165},
}

N. Kumar, P. Pouliquen, and A. Andreou, “Device Mismatch Limitations on the Performance of a Hamming Distance Classifier,” in IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems, 1993.
[BibTeX] [Link]

@inproceedings{18121497,
title = {Device Mismatch Limitations on the Performance of a Hamming Distance Classifier},
author = {{N. Kumar} and {P. Pouliquen} and {A. Andreou}},
year = 1993,
booktitle = {IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems},
url = {https://www.semanticscholar.org/paper/b887f679508e579911529f9312db3e87ef2df7d0},
}

K. Boahen and A. Andreou, “Design of a bidirectional associative memory chip.” 1993.
[BibTeX] [Link]

@inproceedings{63103715,
title = {Design of a bidirectional associative memory chip},
author = {{K. Boahen} and {A. Andreou}},
year = 1993,
month = {8},
booktitle = {},
url = {https://www.semanticscholar.org/paper/14b1998ddcd4a0356c57c5e93884f5d85156cdd4},
}

N. Kumar, P. Pouliquen, and A. Andreou, “Device mismatch limitations on the performance of an associative memory system,” in Proceedings of 36th Midwest Symposium on Circuits and Systems, 1993.
[BibTeX] [Link]

@inproceedings{62679226,
title = {Device mismatch limitations on the performance of an associative memory system},
author = {{N. Kumar} and {P. Pouliquen} and {A. Andreou}},
year = 1993,
month = {8},
booktitle = {Proceedings of 36th Midwest Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/147f85bea71d8dfc311c912b6f1f40e2270e18c9},
}

A. Andreou, “Analog VLSI neuromorphic systems,” in 1993 IEEE International Symposium on Circuits and Systems, 1993.
[BibTeX] [Link]

@inproceedings{10684271,
title = {Analog VLSI neuromorphic systems},
author = {{A. Andreou}},
year = 1993,
month = {5},
booktitle = {1993 IEEE International Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/87d8eb1b50654db206f34f5bdc9ec2f855c2ba8a},
}

P. Pouliquen, A. Andreou, K. Strohbehn, and R. E. Jenkins, “An associative memory integrated system for character recognition,” in Proceedings of 36th Midwest Symposium on Circuits and Systems, 1993.
[BibTeX] [Link]

@inproceedings{61021358,
title = {An associative memory integrated system for character recognition},
author = {{P. Pouliquen} and {A. Andreou} and {K. Strohbehn} and {R. E. Jenkins}},
year = 1993,
month = {8},
booktitle = {Proceedings of 36th Midwest Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/420f65dc0310a79a940a73688cdbbc512b844645},
}

Kewei Yang and A. Andreou, “Multiple input floating-gate MOS differential amplifiers and applications for analog computation,” in Proceedings of 36th Midwest Symposium on Circuits and Systems, 1993.
[BibTeX] [Link]

@inproceedings{60557239,
title = {Multiple input floating-gate MOS differential amplifiers and applications for analog computation},
author = {{Kewei Yang} and {A. Andreou}},
year = 1993,
month = {8},
booktitle = {Proceedings of 36th Midwest Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/4328fd8a6e1067a6484653fddadcc752a6e5c0c7},
}

R. C. Meitzler, A. Andreou, K. Strohbehn, and R. E. Jenkins, “A sampled-data motion chip,” in Proceedings of 36th Midwest Symposium on Circuits and Systems, 1993.
[BibTeX] [Link]

@inproceedings{58781669,
title = {A sampled-data motion chip},
author = {{R. C. Meitzler} and {A. Andreou} and {K. Strohbehn} and {R. E. Jenkins}},
year = 1993,
month = {8},
booktitle = {Proceedings of 36th Midwest Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/5fc45836b809fc7c80d51286afac7b6718013bcd},
}

P. Furth and A. Andreou, “A high-drive low-power BiCMOS buffer using compound PMOS/NPN transistors,” in Proceedings of 36th Midwest Symposium on Circuits and Systems, 1993.
[BibTeX] [Link]

@inproceedings{15574609,
title = {A high-drive low-power BiCMOS buffer using compound PMOS/NPN transistors},
author = {{P. Furth} and {A. Andreou}},
year = 1993,
month = {8},
booktitle = {Proceedings of 36th Midwest Symposium on Circuits and Systems},
url = {https://www.semanticscholar.org/paper/0934f27065b1871fd0185124e4f6339c5e1526e1},
}

M. A. Jones and J. M. Eisner, “A Probabilistic Parser Applied to Software Testing Documents,” in Proceedings of National Conference on Artificial Intelligence (AAAI-92), San Jose, 1992, p. 322–328.
[BibTeX] [Link]

@InProceedings{jones-eisner-1992-aaai,
author = "Mark A. Jones and Jason M. Eisner",
title = "A Probabilistic Parser Applied to Software Testing
Documents",
booktitle = "Proceedings of National Conference on Artificial
Intelligence (AAAI-92)",
pages = "322--328",
year = "1992",
month = jul,
address = "San Jose",
URL = "http://cs.jhu.edu/~jason/papers/#jones-eisner-1992-aaai",
}

M. A. Jones and J. M. Eisner, “A Probabilistic Parser and Its Application,” in Statistically-Based Natural Language Processing Techniques: Papers from the 1992 Workshop, 1992, p. 20–27.
[BibTeX] [Link]

@InProceedings{jones-eisner-1992-workshop,
author = "Mark A. Jones and Jason M. Eisner",
title = "A Probabilistic Parser and Its Application",
booktitle = "Statistically-Based Natural Language Processing
Techniques: Papers from the 1992 Workshop",
editor = "Carl Weir",
pages = "20--27",
year = "1992",
month = jul,
publisher = "Menlo Park: AAAI Press",
note = "Technical Report WS-92-01",
URL = "http://cs.jhu.edu/~jason/papers/#jones-eisner-1992-workshop",
}

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