Papers
Adversarial Examples Exist in Two-Layer ReLU Networks for Low Dimensional Linear Subspaces
Odelia Melamed, Gilad Yehudai, Gal Vardi
Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness
Ambar Pal, Jeremias Sulam, Rene Vidal
Adversarial Learning for Feature Shift Detection and Correction
Míriam Barrabés, Daniel Mas Montserrat, Margarita Geleta et al.
Adversarially Robust Distributed Count Tracking via Partial Differential Privacy
Zhongzheng Xiong, Xiaoyi Zhu, zengfeng Huang
Adversarially Robust Learning with Uncertain Perturbation Sets
Tosca Lechner, Vinayak Pathak, Ruth Urner
Adversarial Model for Offline Reinforcement Learning
Mohak Bhardwaj, Tengyang Xie, Byron Boots et al.
Adversarial Resilience in Sequential Prediction via Abstention
Surbhi Goel, Steve Hanneke, Shay Moran et al.
Adversarial Robustness in Graph Neural Networks: A Hamiltonian Approach
Kai Zhao, Qiyu Kang, Yang Song et al.
Adversarial Robustness through Random Weight Sampling
Yanxiang Ma, Minjing Dong, Chang Xu
Adversarial Self-Training Improves Robustness and Generalization for Gradual Domain Adaptation
Lianghe Shi, Weiwei Liu
Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions
Lukas Gosch, Simon Geisler, Daniel Sturm et al.
Adversarial Training from Mean Field Perspective
Soichiro Kumano, Hiroshi Kera, Toshihiko Yamasaki
Advice Querying under Budget Constraint for Online Algorithms
Ziyad Benomar, Vianney Perchet
A Dynamical System View of Langevin-Based Non-Convex Sampling
Mohammad Reza Karimi Jaghargh, Ya-Ping Hsieh, Andreas Krause
A Fast and Accurate Estimator for Large Scale Linear Model via Data Averaging
Rui Wang, Yanyan Ouyang, Yu Panpan et al.
A fast heuristic to optimize time-space tradeoff for large models
Akifumi Imanishi, Zijian Xu, Masayuki Takagi et al.
Affinity-Aware Graph Networks
Ameya Velingker, Ali Sinop, Ira Ktena et al.
A Finite-Particle Convergence Rate for Stein Variational Gradient Descent
Jiaxin Shi, Lester W. Mackey
A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games
Zaiwei Chen, Kaiqing Zhang, Eric Mazumdar et al.
A Fractional Graph Laplacian Approach to Oversmoothing
Sohir Maskey, Raffaele Paolino, Aras Bacho et al.
A Framework for Fast and Stable Representations of Multiparameter Persistent Homology Decompositions
David Loiseaux, Mathieu Carrière, Andrew Blumberg
AGD: an Auto-switchable Optimizer using Stepwise Gradient Difference for Preconditioning Matrix
Yun Yue, Zhiling Ye, Jiadi Jiang et al.
A General Framework for Equivariant Neural Networks on Reductive Lie Groups
Ilyes Batatia, Mario Geiger, Jose Munoz et al.
A General Framework for Robust G-Invariance in G-Equivariant Networks
Sophia Sanborn, Nina Miolane
A General Theory of Correct, Incorrect, and Extrinsic Equivariance
Dian Wang, Xupeng Zhu, Jung Yeon Park et al.