Papers
Graph Element Networks: adaptive, structured computation and memory
Ferran Alet, Adarsh Keshav Jeewajee, Maria Bauza Villalonga et al.
Multi-objective training of Generative Adversarial Networks with multiple discriminators
Isabela Albuquerque, Joao Monteiro, Thang Doan et al.
Validating Causal Inference Models via Influence Functions
Ahmed Alaa, Mihaela Van Der Schaar
Projections for Approximate Policy Iteration Algorithms
Riad Akrour, Joni Pajarinen, Jan Peters et al.
Adaptive Stochastic Natural Gradient Method for One-Shot Neural Architecture Search
Youhei Akimoto, Shinichi Shirakawa, Nozomu Yoshinari et al.
Fairwashing: the risk of rationalization
Ulrich Aivodji, Hiromi Arai, Olivier Fortineau et al.
Understanding the Impact of Entropy on Policy Optimization
Zafarali Ahmed, Nicolas Le Roux, Mohammad Norouzi et al.
The Kernel Interaction Trick: Fast Bayesian Discovery of Pairwise Interactions in High Dimensions
Raj Agrawal, Brian Trippe, Jonathan Huggins et al.
Learning to Generalize from Sparse and Underspecified Rewards
Rishabh Agarwal, Chen Liang, Dale Schuurmans et al.
Fair Regression: Quantitative Definitions and Reduction-Based Algorithms
Alekh Agarwal, Miroslav Dudik, Zhiwei Steven Wu
Online Control with Adversarial Disturbances
Naman Agarwal, Brian Bullins, Elad Hazan et al.
Efficient Full-Matrix Adaptive Regularization
Naman Agarwal, Brian Bullins, Xinyi Chen et al.
Static Automatic Batching In TensorFlow
Ashish Agarwal
PAC Learnability of Node Functions in Networked Dynamical Systems
Abhijin Adiga, Chris J Kuhlman, Madhav Marathe et al.
TibGM: A Transferable and Information-Based Graphical Model Approach for Reinforcement Learning
Tameem Adel, Adrian Weller
Learning Models from Data with Measurement Error: Tackling Underreporting
Roy Adams, Yuelong Ji, Xiaobin Wang et al.
Communication Complexity in Locally Private Distribution Estimation and Heavy Hitters
Jayadev Acharya, Ziteng Sun
Distributed Learning with Sublinear Communication
Jayadev Acharya, Chris De Sa, Dylan Foster et al.
Communication-Constrained Inference and the Role of Shared Randomness
Jayadev Acharya, Clement Canonne, Himanshu Tyagi
MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing
Sami Abu-El-Haija, Bryan Perozzi, Amol Kapoor et al.
Dynamic Weights in Multi-Objective Deep Reinforcement Learning
Axel Abels, Diederik Roijers, Tom Lenaerts et al.
AReS and MaRS Adversarial and MMD-Minimizing Regression for SDEs
Gabriele Abbati, Philippe Wenk, Michael A. Osborne et al.
Smoothing the Geometry of Probabilistic Box Embeddings
Xiang Li, Luke Vilnis, Dongxu Zhang et al.
Training for Faster Adversarial Robustness Verification via Inducing ReLU Stability
Kai Y. Xiao, Vincent Tjeng, Nur Muhammad (Mahi) Shafiullah et al.