David Belanger

Publication Activity (10 Years)

Years Active: 1999-2022
Publications (10 Years): 33

Top Topics

Structured Prediction

Relation Extraction

Sequence Labeling

Top Venues

Publications

Theodore P. Papalexopoulos, Christian Tjandraatmadja, Ross Anderson, Juan Pablo Vielma, David Belanger
Constrained Discrete Black-Box Optimization using Mixed-Integer Programming. ICML (2022)
David Dohan, Andreea Gane, Maxwell L. Bileschi, David Belanger, Lucy J. Colwell
Improving Protein Function Annotation via Unsupervised Pre-training: Robustness, Efficiency, and Insights. KDD (2021)
Sherry Chao, David Belanger
Generalizing Few-Shot Classification of Whole-Genome Doubling Across Cancer Types. ICCVW (2021)
Ye Ouyang, Lilei Wang, Aidong Yang, Le Su, David Belanger, Tongqing Gao, Leping Wei, Yaqin Zhang
The Next Decade of Telecommunications Artificial Intelligence. CoRR (2021)
Amir Shanehsazzadeh, David Belanger, David Dohan
Is Transfer Learning Necessary for Protein Landscape Prediction? CoRR (2020)
Chen Liu, William Bill Rouse, David Belanger
Understanding Risks and Opportunities of Autonomous Vehicle Technology Adoption Through Systems Dynamic Scenario Modeling - The American Insurance Industry. IEEE Syst. J. 14 (1) (2020)
Amir Shanehsazzadeh, David Belanger, David Dohan
Fixed-Length Protein Embeddings using Contextual Lenses. CoRR (2020)
Christof Angermüller, David Dohan, David Belanger, Ramya Deshpande, Kevin Murphy, Lucy J. Colwell
Model-based reinforcement learning for biological sequence design. ICLR (2020)
Christof Angermüller, David Belanger, Andreea Gane, Zelda Mariet, David Dohan, Kevin Murphy, Lucy J. Colwell, D. Sculley
Population-Based Black-Box Optimization for Biological Sequence Design. CoRR (2020)
Christof Angermüller, David Belanger, Andreea Gane, Zelda Mariet, David Dohan, Kevin Murphy, Lucy J. Colwell, D. Sculley
Population-Based Black-Box Optimization for Biological Sequence Design. ICML (2020)
Brandon Carter, Maxwell L. Bileschi, Jamie Smith, Theo Sanderson, Drew Bryant, David Belanger, Lucy J. Colwell
Critiquing Protein Family Classification Models Using Sufficient Input Subsets. J. Comput. Biol. 27 (8) (2020)
Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Jared Davis, Tamás Sarlós, David Belanger, Lucy J. Colwell, Adrian Weller
Masked Language Modeling for Proteins via Linearly Scalable Long-Context Transformers. CoRR (2020)
Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Andreea Gane, Tamás Sarlós, Peter Hawkins, Jared Davis, Afroz Mohiuddin, Lukasz Kaiser, David Belanger, Lucy J. Colwell, Adrian Weller
Rethinking Attention with Performers. CoRR (2020)
Dilip Krishnan, Piotr Teterwak, Aaron Sarna, Aaron Maschinot, Ce Liu, David Belanger, William T. Freeman
Boundless: Generative Adversarial Networks for Image Extension. ICCV (2019)
Piotr Teterwak, Aaron Sarna, Dilip Krishnan, Aaron Maschinot, David Belanger, Ce Liu, William T. Freeman
Boundless: Generative Adversarial Networks for Image Extension. CoRR (2019)
Gonzalo E. Mena, David Belanger, Scott W. Linderman, Jasper Snoek
Learning Latent Permutations with Gumbel-Sinkhorn Networks. CoRR (2018)
Gonzalo E. Mena, David Belanger, Scott W. Linderman, Jasper Snoek
Learning Latent Permutations with Gumbel-Sinkhorn Networks. ICLR (Poster) (2018)
Dung Thai, Shikhar Murty, Trapit Bansal, Luke Vilnis, David Belanger, Andrew McCallum
Low-Rank Hidden State Embeddings for Viterbi Sequence Labeling. CoRR (2017)
Rajarshi Das, Arvind Neelakantan, David Belanger, Andrew McCallum
Chains of Reasoning over Entities, Relations, and Text using Recurrent Neural Networks. EACL (1) (2017)
Emma Strubell, Patrick Verga, David Belanger, Andrew McCallum
Fast and Accurate Entity Recognition with Iterated Dilated Convolutions. EMNLP (2017)
David Belanger, Bishan Yang, Andrew McCallum
End-to-End Learning for Structured Prediction Energy Networks. ICML (2017)
Forrester Cole, David Belanger, Dilip Krishnan, Aaron Sarna, Inbar Mosseri, William T. Freeman
Face Synthesis from Facial Identity Features. CoRR (2017)
David Belanger, Bishan Yang, Andrew McCallum
End-to-End Learning for Structured Prediction Energy Networks. CoRR (2017)
Emma Strubell, Patrick Verga, David Belanger, Andrew McCallum
Fast and Accurate Sequence Labeling with Iterated Dilated Convolutions. CoRR (2017)
Forrester Cole, David Belanger, Dilip Krishnan, Aaron Sarna, Inbar Mosseri, William T. Freeman
Synthesizing Normalized Faces from Facial Identity Features. CVPR (2017)
Harvey Freeman, David Belanger
Communications, ComSoc, and Big Data: What and What Next? IEEE Commun. Mag. 55 (2) (2017)
David Belanger, Andrew McCallum
Structured Prediction Energy Networks. ICML (2016)
Patrick Verga, David Belanger, Emma Strubell, Benjamin Roth, Andrew McCallum
Multilingual Relation Extraction using Compositional Universal Schema. HLT-NAACL (2016)
Rajarshi Das, Arvind Neelakantan, David Belanger, Andrew McCallum
Chains of Reasoning over Entities, Relations, and Text using Recurrent Neural Networks. CoRR (2016)
Trapit Bansal, David Belanger, Andrew McCallum
Ask the GRU: Multi-Task Learning for Deep Text Recommendations. CoRR (2016)
Kui Tang, Nicholas Ruozzi, David Belanger, Tony Jebara
Bethe Learning of Graphical Models via MAP Decoding. AISTATS (2016)
Rajarshi Das, Arvind Neelakantan, David Belanger, Andrew McCallum
Incorporating Selectional Preferences in Multi-hop Relation Extraction. AKBC@NAACL-HLT (2016)
Trapit Bansal, David Belanger, Andrew McCallum
: Multi-task Learning for Deep Text Recommendations. RecSys (2016)
David Belanger, Sham M. Kakade
A Linear Dynamical System Model for Text. CoRR (2015)
David Belanger, Andrew McCallum
Structured Prediction Energy Networks. CoRR (2015)
Patrick Verga, David Belanger, Emma Strubell, Benjamin Roth, Andrew McCallum
Multilingual Relation Extraction using Compositional Universal Schema. CoRR (2015)
Luke Vilnis, David Belanger, Daniel Sheldon, Andrew McCallum
Bethe Projections for Non-Local Inference. CoRR (2015)
David Belanger, Sham M. Kakade
A Linear Dynamical System Model for Text. ICML (2015)
Benjamin Roth, Nicholas Monath, David Belanger, Emma Strubell, Patrick Verga, Andrew McCallum
Building Knowledge Bases with Universal Schema: Cold Start and Slot-Filling Approaches. TAC (2015)
Luke Vilnis, David Belanger, Daniel Sheldon, Andrew McCallum
Bethe Projections for Non-Local Inference. UAI (2015)
Kui Tang, Nicholas Ruozzi, David Belanger, Tony Jebara
Bethe Learning of Conditional Random Fields via MAP Decoding. CoRR (2015)
Huaigu Cao, Prem Natarajan, Xujun Peng, Krishna Subramanian, David Belanger, Nan Li
Progress in the Raytheon BBN Arabic Offline Handwriting Recognition System. ICFHR (2014)
Sam Anzaroot, Alexandre Passos, David Belanger, Andrew McCallum
Learning Soft Linear Constraints with Application to Citation Field Extraction. ACL (1) (2014)
Sam Anzaroot, Alexandre Passos, David Belanger, Andrew McCallum
Learning Soft Linear Constraints with Application to Citation Field Extraction. CoRR (2014)
David Belanger, Alexandre Passos, Sebastian Riedel, Andrew McCallum
Message Passing for Soft Constraint Dual Decomposition. UAI (2014)
Sameer Singh, Limin Yao, David Belanger, Ari Kobren, Sam Anzaroot, Mike Wick, Alexandre Passos, Harshal Pandya, Jinho D. Choi, Brian Martin, Andrew McCallum
Universal Schema for Slot Filling and Cold Start: UMass IESL at TACKBP 2013. TAC (2013)
David Belanger, Alexandre Passos, Sebastian Riedel, Andrew McCallum
MAP Inference in Chains using Column Generation. NIPS (2012)
Pradeep Natarajan, David Belanger, Rohit Prasad, Matin Kamali, Krishna Subramanian, Prem Natarajan
Baseline Dependent Percentile Features for Offline Arabic Handwriting Recognition. ICDAR (2011)
Rohit Prasad, Matin Kamali, David Belanger, Antti-Veikko I. Rosti, Spyros Matsoukas, Prem Natarajan
Consensus Network Based Hypotheses Combination for Arabic Offline Handwriting Recognition. ICPR (2010)
David Belanger, Kenneth Ward Church, Andrew Hume
Virtual Data Warehousing, Data Publishing, and Call Detail. Databases in Telecommunications (1999)