|
Poster
|
|
Achieve the Minimum Width of Neural Networks for Universal Approximation
Yongqiang Cai
|
|
|
Poster
|
|
Offline Reinforcement Learning with Differentiable Function Approximation is Provably Efficient
Ming Yin · Mengdi Wang · Yu-Xiang Wang
|
|
|
Poster
|
|
Near-Optimal Deployment Efficiency in Reward-Free Reinforcement Learning with Linear Function Approximation
Dan Qiao · Yu-Xiang Wang
|
|
|
Poster
|
Mon 7:30
|
Constructive TT-representation of the tensors given as index interaction functions with applications
Gleb Ryzhakov · Ivan Oseledets
|
|
|
Poster
|
|
Optimal Conservative Offline RL with General Function Approximation via Augmented Lagrangian
Paria Rashidinejad · Hanlin Zhu · Kunhe Yang · Stuart Russell · Jiantao Jiao
|
|
|
Poster
|
|
The Role of Coverage in Online Reinforcement Learning
Tengyang Xie · Dylan Foster · Yu Bai · Nan Jiang · Sham Kakade
|
|
|
Poster
|
|
Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game
Wei Xiong · Han Zhong · Chengshuai Shi · Cong Shen · Liwei Wang · Tong Zhang
|
|
|
Workshop
|
Thu 5:00
|
Diffusion Models are Minimax Optimal Distribution Estimators
Kazusato Oko · Akiyama Shunta · Taiji Suzuki
|
|
|
Workshop
|
Thu 4:00
|
Diffusion Models are Minimax Optimal Distribution Estimators
Kazusato Oko · Akiyama Shunta · Taiji Suzuki
|
|
|
Poster
|
Tue 7:30
|
The Implicit Bias of Minima Stability in Multivariate Shallow ReLU Networks
Mor Shpigel Nacson · Rotem Mulayoff · Greg Ongie · Tomer Michaeli · Daniel Soudry
|
|
|
Poster
|
|
Learning Adversarial Linear Mixture Markov Decision Processes with Bandit Feedback and Unknown Transition
Canzhe Zhao · Ruofeng Yang · Baoxiang Wang · Shuai Li
|
|
|
Poster
|
|
Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds using Deep Networks
Xiang Ji · Minshuo Chen · Mengdi Wang · Tuo Zhao
|
|
