Papers
A Feasible Level Proximal Point Method for Nonconvex Sparse Constrained Optimization
Digvijay Boob, Qi Deng, Guanghui Lan et al.
A Finite-Time Analysis of Two Time-Scale Actor-Critic Methods
Yue Frank Wu, Weitong ZHANG, Pan Xu et al.
A Flexible Framework for Designing Trainable Priors with Adaptive Smoothing and Game Encoding
Bruno Lecouat, Jean Ponce, Julien Mairal
A Game Theoretic Analysis of Additive Adversarial Attacks and Defenses
Ambar Pal, Rene Vidal
A game-theoretic analysis of networked system control for common-pool resource management using multi-agent reinforcement learning
Arnu Pretorius, Scott Cameron, Elan van Biljon et al.
A Game-Theoretic Analysis of the Empirical Revenue Maximization Algorithm with Endogenous Sampling
Xiaotie Deng, Ron Lavi, Tao Lin et al.
A Generalized Neural Tangent Kernel Analysis for Two-layer Neural Networks
Zixiang Chen, Yuan Cao, Quanquan Gu et al.
A General Large Neighborhood Search Framework for Solving Integer Linear Programs
Jialin Song, ravi lanka, Yisong Yue et al.
A General Method for Robust Learning from Batches
Ayush Jain, Alon Orlitsky
Agnostic $Q$-learning with Function Approximation in Deterministic Systems: Near-Optimal Bounds on Approximation Error and Sample Complexity
Simon S Du, Jason Lee, Gaurav Mahajan et al.
Agnostic Learning of a Single Neuron with Gradient Descent
Spencer Frei, Yuan Cao, Quanquan Gu
Agnostic Learning with Multiple Objectives
Corinna Cortes, Mehryar Mohri, Javier Gonzalvo et al.
A graph similarity for deep learning
Seongmin Ok
Agree to Disagree: Adaptive Ensemble Knowledge Distillation in Gradient Space
Shangchen Du, Shan You, Xiaojie Li et al.
A Group-Theoretic Framework for Data Augmentation
Shuxiao Chen, Edgar Dobriban, Jane Lee
AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity
Silviu-Marian Udrescu, Andrew Tan, Jiahai Feng et al.
A kernel test for quasi-independence
Tamara Fernandez, Wenkai Xu, Marc Ditzhaus et al.
Algorithmic recourse under imperfect causal knowledge: a probabilistic approach
Amir-Hossein Karimi, Julius von Kügelgen, Bernhard Schölkopf et al.
A Limitation of the PAC-Bayes Framework
Roi Livni, Shay Moran
All-or-nothing statistical and computational phase transitions in sparse spiked matrix estimation
jean barbier, Nicolas Macris, Cynthia Rush
All Word Embeddings from One Embedding
Sho Takase, Sosuke Kobayashi
All your loss are belong to Bayes
Christian Walder, Richard Nock
Almost Optimal Model-Free Reinforcement Learningvia Reference-Advantage Decomposition
Zihan Zhang, Yuan Zhou, Xiangyang Ji
Almost Surely Stable Deep Dynamics
Nathan Lawrence, Philip Loewen, Michael Forbes et al.
A Local Temporal Difference Code for Distributional Reinforcement Learning
Pablo Tano, Peter Dayan, Alexandre Pouget