Papers
Addressing Sample Complexity in Visual Tasks Using HER and Hallucinatory GANs
Himanshu Sahni, Toby Buckley, Pieter Abbeel et al.
A Debiased MDI Feature Importance Measure for Random Forests
Xiao Li, Yu Wang, Sumanta Basu et al.
A Direct tilde{O}(1/epsilon) Iteration Parallel Algorithm for Optimal Transport
Arun Jambulapati, Aaron Sidford, Kevin Tian
A Domain Agnostic Measure for Monitoring and Evaluating GANs
Paulina Grnarova, Kfir Y. Levy, Aurelien Lucchi et al.
Adversarial Examples Are Not Bugs, They Are Features
Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras et al.
Adversarial Fisher Vectors for Unsupervised Representation Learning
Shuangfei Zhai, Walter Talbott, Carlos Guestrin et al.
Adversarial Music: Real world Audio Adversary against Wake-word Detection System
Juncheng Li, Shuhui Qu, Xinjian Li et al.
Adversarial Robustness through Local Linearization
Chongli Qin, James Martens, Sven Gowal et al.
Adversarial Self-Defense for Cycle-Consistent GANs
Dina Bashkirova, Ben Usman, Kate Saenko
Adversarial Training and Robustness for Multiple Perturbations
Florian Tramer, Dan Boneh
Adversarial training for free!
Ali Shafahi, Mahyar Najibi, Mohammad Amin Ghiasi et al.
A Family of Robust Stochastic Operators for Reinforcement Learning
Yingdong Lu, Mark Squillante, Chai Wah Wu
A First-Order Algorithmic Framework for Distributionally Robust Logistic Regression
JIAJIN LI, SEN HUANG, Anthony Man-Cho So
A Flexible Generative Framework for Graph-based Semi-supervised Learning
Jiaqi Ma, Weijing Tang, Ji Zhu et al.
A Fourier Perspective on Model Robustness in Computer Vision
Dong Yin, Raphael Gontijo Lopes, Jon Shlens et al.
A Game Theoretic Approach to Class-wise Selective Rationalization
Shiyu Chang, Yang Zhang, Mo Yu et al.
AGEM: Solving Linear Inverse Problems via Deep Priors and Sampling
Bichuan Guo, Yuxing Han, Jiangtao Wen
A General Framework for Symmetric Property Estimation
Moses Charikar, Kirankumar Shiragur, Aaron Sidford
A Generalized Algorithm for Multi-Objective Reinforcement Learning and Policy Adaptation
Runzhe Yang, Xingyuan Sun, Karthik Narasimhan
A General Theory of Equivariant CNNs on Homogeneous Spaces
Taco S Cohen, Mario Geiger, Maurice Weiler
A Generic Acceleration Framework for Stochastic Composite Optimization
Andrei Kulunchakov, Julien Mairal
A Geometric Perspective on Optimal Representations for Reinforcement Learning
Marc Bellemare, Will Dabney, Robert Dadashi et al.
A Graph Theoretic Additive Approximation of Optimal Transport
Nathaniel Lahn, Deepika Mulchandani, Sharath Raghvendra
A Graph Theoretic Framework of Recomputation Algorithms for Memory-Efficient Backpropagation
Mitsuru Kusumoto, Takuya Inoue, Gentaro Watanabe et al.
A Kernel Loss for Solving the Bellman Equation
Yihao Feng, Lihong Li, Qiang Liu