Papers
Improving Explorability in Variational Inference with Annealed Variational Objectives
Chin-Wei Huang, Shawn Tan, Alexandre Lacoste et al.
Scalable End-to-End Autonomous Vehicle Testing via Rare-event Simulation
Matthew O'Kelly, Aman Sinha, Hongseok Namkoong et al.
Active Matting
Xin Yang, Ke Xu, Shaozhe Chen et al.
Complex Gated Recurrent Neural Networks
Moritz Wolter, Angela Yao
Multivariate Convolutional Sparse Coding for Electromagnetic Brain Signals
Tom Dupré la Tour, Thomas Moreau, Mainak Jas et al.
Mirrored Langevin Dynamics
Ya-Ping Hsieh, Ali Kavis, Paul Rolland et al.
MetaReg: Towards Domain Generalization using Meta-Regularization
Yogesh Balaji, Swami Sankaranarayanan, Rama Chellappa
A Theory-Based Evaluation of Nearest Neighbor Models Put Into Practice
Hendrik Fichtenberger, Dennis Rohde
Connecting Optimization and Regularization Paths
Arun Suggala, Adarsh Prasad, Pradeep K Ravikumar
Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning
Tom Zahavy, Matan Haroush, Nadav Merlis et al.
3D-Aware Scene Manipulation via Inverse Graphics
Shunyu Yao, Tzu Ming Hsu, Jun-Yan Zhu et al.
Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures
Sergey Bartunov, Adam Santoro, Blake Richards et al.
On Coresets for Logistic Regression
Alexander Munteanu, Chris Schwiegelshohn, Christian Sohler et al.
Evolutionary Stochastic Gradient Descent for Optimization of Deep Neural Networks
Xiaodong Cui, Wei Zhang, Zoltán Tüske et al.
A Smoother Way to Train Structured Prediction Models
Venkata Krishna Pillutla, Vincent Roulet, Sham M. Kakade et al.
Stochastic Nonparametric Event-Tensor Decomposition
Shandian Zhe, Yishuai Du
Power-law efficient neural codes provide general link between perceptual bias and discriminability
Michael Morais, Jonathan W Pillow
Neural Proximal Gradient Descent for Compressive Imaging
Morteza Mardani, Qingyun Sun, David Donoho et al.
Learning Hierarchical Semantic Image Manipulation through Structured Representations
Seunghoon Hong, Xinchen Yan, Thomas S. Huang et al.
Adversarially Robust Optimization with Gaussian Processes
Ilija Bogunovic, Jonathan Scarlett, Stefanie Jegelka et al.
An intriguing failing of convolutional neural networks and the CoordConv solution
Rosanne Liu, Joel Lehman, Piero Molino et al.
Non-delusional Q-learning and value-iteration
Tyler Lu, Dale Schuurmans, Craig Boutilier
Towards Understanding Learning Representations: To What Extent Do Different Neural Networks Learn the Same Representation
Liwei Wang, Lunjia Hu, Jiayuan Gu et al.
Joint Sub-bands Learning with Clique Structures for Wavelet Domain Super-Resolution
Zhisheng Zhong, Tiancheng Shen, Yibo Yang et al.
On Oracle-Efficient PAC RL with Rich Observations
Christoph Dann, Nan Jiang, Akshay Krishnamurthy et al.