The Benefits of Being Distributional: Small-Loss Bounds for
Reinforcement Learning

The Benefits of Being Distributional: Small-Loss Bounds for Reinforcement Learning

25 May 2023

Papers citing "The Benefits of Being Distributional: Small-Loss Bounds for Reinforcement Learning"

18 / 18 papers shown

Title
Diffusing States and Matching Scores: A New Framework for Imitation Learning Runzhe Wu Yiding Chen Gokul Swamy Kianté Brantley Wen Sun DiffM 42 3 0 17 Oct 2024
How Does Variance Shape the Regret in Contextual Bandits? Zeyu Jia Jian Qian Alexander Rakhlin Chen-Yu Wei 35 4 0 16 Oct 2024
The Central Role of the Loss Function in Reinforcement Learning Kaiwen Wang Nathan Kallus Wen Sun OffRL 56 7 0 19 Sep 2024
Bellman Unbiasedness: Toward Provably Efficient Distributional Reinforcement Learning with General Value Function Approximation Taehyun Cho Seung Han Kyungjae Lee Seokhun Ju Dohyeong Kim Jungwoo Lee 64 0 0 31 Jul 2024
REBEL: Reinforcement Learning via Regressing Relative Rewards Zhaolin Gao Jonathan D. Chang Wenhao Zhan Owen Oertell Gokul Swamy Kianté Brantley Thorsten Joachims J. Andrew Bagnell Jason D. Lee Wen Sun OffRL 40 31 0 25 Apr 2024
Efficient and Sharp Off-Policy Evaluation in Robust Markov Decision Processes Andrew Bennett Nathan Kallus M. Oprescu Wen Sun Kaiwen Wang AAML OffRL 50 1 0 29 Mar 2024
Stop Regressing: Training Value Functions via Classification for Scalable Deep RL Jesse Farebrother Jordi Orbay Q. Vuong Adrien Ali Taïga Yevgen Chebotar ... Sergey Levine Pablo Samuel Castro Aleksandra Faust Aviral Kumar Rishabh Agarwal OffRL 56 56 0 06 Mar 2024
Provable Risk-Sensitive Distributional Reinforcement Learning with General Function Approximation Yu Chen Xiangcheng Zhang Siwei Wang Longbo Huang 42 3 0 28 Feb 2024
Towards Robust Model-Based Reinforcement Learning Against Adversarial Corruption Chen Ye Jiafan He Quanquan Gu Tong Zhang 48 5 0 14 Feb 2024
Near-Minimax-Optimal Distributional Reinforcement Learning with a Generative Model Mark Rowland Wenliang Kevin Li Rémi Munos Clare Lyle Yunhao Tang Will Dabney OOD OffRL 30 1 0 12 Feb 2024
More Benefits of Being Distributional: Second-Order Bounds for Reinforcement Learning Kaiwen Wang Owen Oertell Alekh Agarwal Nathan Kallus Wen Sun OffRL 88 12 0 11 Feb 2024
Settling the Sample Complexity of Online Reinforcement Learning Zihan Zhang Yuxin Chen Jason D. Lee S. Du OffRL 98 21 0 25 Jul 2023
Distributional Reinforcement Learning by Sinkhorn Divergence Ke Sun Yingnan Zhao Wulong Liu Bei Jiang Linglong Kong 27 0 0 01 Feb 2022
First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach Andrew Wagenmaker Yifang Chen Max Simchowitz S. Du Kevin G. Jamieson 73 36 0 07 Dec 2021
Pessimistic Model-based Offline Reinforcement Learning under Partial Coverage Masatoshi Uehara Wen Sun OffRL 96 144 0 13 Jul 2021
Conservative Offline Distributional Reinforcement Learning Yecheng Jason Ma Dinesh Jayaraman Osbert Bastani OffRL 70 78 0 12 Jul 2021
Model-free Representation Learning and Exploration in Low-rank MDPs Aditya Modi Jinglin Chen A. Krishnamurthy Nan Jiang Alekh Agarwal OffRL 102 78 0 14 Feb 2021
Reward-Free Exploration for Reinforcement Learning Chi Jin A. Krishnamurthy Max Simchowitz Tiancheng Yu OffRL 112 194 0 07 Feb 2020