Belanger, David

13 publications

ICML 2022 Constrained Discrete Black-Box Optimization Using Mixed-Integer Programming Theodore P Papalexopoulos, Christian Tjandraatmadja, Ross Anderson, Juan Pablo Vielma, David Belanger

ICCVW 2021 Generalizing Few-Shot Classification of Whole-Genome Doubling Across Cancer Types Sherry Chao, David Belanger

ICLR 2020 Model-Based Reinforcement Learning for Biological Sequence Design Christof Angermueller, David Dohan, David Belanger, Ramya Deshpande, Kevin Murphy, Lucy Colwell

ICML 2020 Population-Based Black-Box Optimization for Biological Sequence Design Christof Angermueller, David Belanger, Andreea Gane, Zelda Mariet, David Dohan, Kevin Murphy, Lucy Colwell, D Sculley

ICLR 2018 Learning Latent Permutations with Gumbel-Sinkhorn Networks Gonzalo Mena, David Belanger, Scott Linderman, Jasper Snoek

ICML 2017 End-to-End Learning for Structured Prediction Energy Networks David Belanger, Bishan Yang, Andrew McCallum

CVPR 2017 Synthesizing Normalized Faces from Facial Identity Features Forrester Cole, David Belanger, Dilip Krishnan, Aaron Sarna, Inbar Mosseri, William T. Freeman

AISTATS 2016 Bethe Learning of Graphical Models via MAP Decoding Kui Tang, Nicholas Ruozzi, David Belanger, Tony Jebara

ICML 2016 Structured Prediction Energy Networks David Belanger, Andrew McCallum

ICML 2015 A Linear Dynamical System Model for Text David Belanger, Sham Kakade

UAI 2015 Bethe Projections for Non-Local Inference Luke Vilnis, David Belanger, Daniel Sheldon, Andrew McCallum

UAI 2014 Message Passing for Soft Constraint Dual Decomposition David Belanger, Alexandre Passos, Sebastian Riedel, Andrew McCallum

NeurIPS 2012 MAP Inference in Chains Using Column Generation David Belanger, Alexandre Passos, Sebastian Riedel, Andrew McCallum