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Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes

Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes

Jiafan He
Heyang Zhao
Dongruo Zhou
Quanquan Gu
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Papers citing "Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes"

47 / 47 papers shown
Title
Towards Optimal Differentially Private Regret Bounds in Linear MDPs
Towards Optimal Differentially Private Regret Bounds in Linear MDPs
Sharan Sahu
55
0
0
12 Apr 2025
Minimax Optimal Reinforcement Learning with Quasi-Optimism
Harin Lee
Min-hwan Oh
OffRL
59
0
0
02 Mar 2025
Catoni Contextual Bandits are Robust to Heavy-tailed Rewards
Catoni Contextual Bandits are Robust to Heavy-tailed Rewards
Chenlu Ye
Yujia Jin
Alekh Agarwal
Tong Zhang
98
0
0
04 Feb 2025
Provably Efficient Reinforcement Learning with Multinomial Logit Function Approximation
Provably Efficient Reinforcement Learning with Multinomial Logit Function Approximation
Long-Fei Li
Yu-Jie Zhang
Peng Zhao
Zhi-Hua Zhou
99
4
0
17 Jan 2025
Efficient, Low-Regret, Online Reinforcement Learning for Linear MDPs
Philips George John
Arnab Bhattacharyya
Silviu Maniu
Dimitrios Myrisiotis
Zhenan Wu
OffRL
31
0
0
16 Nov 2024
Robust Thompson Sampling Algorithms Against Reward Poisoning Attacks
Robust Thompson Sampling Algorithms Against Reward Poisoning Attacks
Yinglun Xu
Zhiwei Wang
Gagandeep Singh
AAML
23
0
0
25 Oct 2024
Learning Infinite-Horizon Average-Reward Linear Mixture MDPs of Bounded Span
Learning Infinite-Horizon Average-Reward Linear Mixture MDPs of Bounded Span
Woojin Chae
Kihyuk Hong
Yufan Zhang
Ambuj Tewari
Dabeen Lee
32
1
0
19 Oct 2024
Upper and Lower Bounds for Distributionally Robust Off-Dynamics Reinforcement Learning
Upper and Lower Bounds for Distributionally Robust Off-Dynamics Reinforcement Learning
Zhishuai Liu
Weixin Wang
Pan Xu
33
1
0
30 Sep 2024
Hybrid Reinforcement Learning Breaks Sample Size Barriers in Linear MDPs
Hybrid Reinforcement Learning Breaks Sample Size Barriers in Linear MDPs
Kevin Tan
Wei Fan
Yuting Wei
OffRL
69
2
0
08 Aug 2024
Multiple Greedy Quasi-Newton Methods for Saddle Point Problems
Multiple Greedy Quasi-Newton Methods for Saddle Point Problems
Minheng Xiao
Shi Bo
Zhizhong Wu
30
5
0
01 Aug 2024
Bellman Unbiasedness: Toward Provably Efficient Distributional Reinforcement Learning with General Value Function Approximation
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
Warm-up Free Policy Optimization: Improved Regret in Linear Markov Decision Processes
Warm-up Free Policy Optimization: Improved Regret in Linear Markov Decision Processes
Asaf B. Cassel
Aviv A. Rosenberg
35
1
0
03 Jul 2024
Linear Bellman Completeness Suffices for Efficient Online Reinforcement Learning with Few Actions
Linear Bellman Completeness Suffices for Efficient Online Reinforcement Learning with Few Actions
Noah Golowich
Ankur Moitra
OffRL
30
1
0
17 Jun 2024
Reinforcement Learning for Infinite-Horizon Average-Reward Linear MDPs via Approximation by Discounted-Reward MDPs
Reinforcement Learning for Infinite-Horizon Average-Reward Linear MDPs via Approximation by Discounted-Reward MDPs
Kihyuk Hong
Yufan Zhang
Ambuj Tewari
Dabeen Lee
Ambuj Tewari
37
2
0
23 May 2024
Imitation Learning in Discounted Linear MDPs without exploration assumptions
Imitation Learning in Discounted Linear MDPs without exploration assumptions
Luca Viano
Stratis Skoulakis
V. Cevher
30
3
0
03 May 2024
Sample-efficient Learning of Infinite-horizon Average-reward MDPs with General Function Approximation
Sample-efficient Learning of Infinite-horizon Average-reward MDPs with General Function Approximation
Jianliang He
Han Zhong
Zhuoran Yang
38
6
0
19 Apr 2024
Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithm
Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithm
Miao Lu
Han Zhong
Tong Zhang
Jose H. Blanchet
OffRL
OOD
73
4
0
04 Apr 2024
Sample Complexity of Offline Distributionally Robust Linear Markov Decision Processes
Sample Complexity of Offline Distributionally Robust Linear Markov Decision Processes
He Wang
Laixi Shi
Yuejie Chi
OffRL
36
6
0
19 Mar 2024
Horizon-Free Regret for Linear Markov Decision Processes
Horizon-Free Regret for Linear Markov Decision Processes
Zihan Zhang
Jason D. Lee
Yuxin Chen
Simon S. Du
33
3
0
15 Mar 2024
Distributionally Robust Off-Dynamics Reinforcement Learning: Provable Efficiency with Linear Function Approximation
Distributionally Robust Off-Dynamics Reinforcement Learning: Provable Efficiency with Linear Function Approximation
Zhishuai Liu
Pan Xu
OOD
OffRL
39
8
0
23 Feb 2024
Reinforcement Learning from Human Feedback with Active Queries
Reinforcement Learning from Human Feedback with Active Queries
Kaixuan Ji
Jiafan He
Quanquan Gu
18
17
0
14 Feb 2024
Sample Complexity Characterization for Linear Contextual MDPs
Sample Complexity Characterization for Linear Contextual MDPs
Junze Deng
Yuan-Chia Cheng
Shaofeng Zou
Yingbin Liang
30
1
0
05 Feb 2024
Near-Optimal Reinforcement Learning with Self-Play under Adaptivity Constraints
Near-Optimal Reinforcement Learning with Self-Play under Adaptivity Constraints
Dan Qiao
Yu-Xiang Wang
OffRL
24
3
0
02 Feb 2024
A Policy Gradient Primal-Dual Algorithm for Constrained MDPs with Uniform PAC Guarantees
A Policy Gradient Primal-Dual Algorithm for Constrained MDPs with Uniform PAC Guarantees
Toshinori Kitamura
Tadashi Kozuno
Masahiro Kato
Yuki Ichihara
Soichiro Nishimori
Akiyoshi Sannai
Sho Sonoda
Wataru Kumagai
Yutaka Matsuo
37
2
0
31 Jan 2024
Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback
Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback
Canzhe Zhao
Ruofeng Yang
Baoxiang Wang
Xuezhou Zhang
Shuai Li
22
2
0
14 Nov 2023
Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation
Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation
Nikki Lijing Kuang
Ming Yin
Mengdi Wang
Yu-Xiang Wang
Yian Ma
24
6
0
29 Oct 2023
Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement Learning
Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement Learning
Qiwei Di
Heyang Zhao
Jiafan He
Quanquan Gu
OffRL
53
5
0
02 Oct 2023
Minimax Optimal Q Learning with Nearest Neighbors
Minimax Optimal Q Learning with Nearest Neighbors
Puning Zhao
Lifeng Lai
OffRL
49
10
0
03 Aug 2023
Provably Efficient Iterated CVaR Reinforcement Learning with Function Approximation and Human Feedback
Provably Efficient Iterated CVaR Reinforcement Learning with Function Approximation and Human Feedback
Yu Chen
Yihan Du
Pihe Hu
Si-Yi Wang
De-hui Wu
Longbo Huang
24
6
0
06 Jul 2023
On the Model-Misspecification in Reinforcement Learning
On the Model-Misspecification in Reinforcement Learning
Yunfan Li
Lin F. Yang
36
5
0
19 Jun 2023
Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds
Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds
Jiayi Huang
Han Zhong
Liwei Wang
Lin F. Yang
22
6
0
12 Jun 2023
Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo
Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo
Haque Ishfaq
Qingfeng Lan
Pan Xu
A. R. Mahmood
Doina Precup
Anima Anandkumar
Kamyar Azizzadenesheli
BDL
OffRL
26
20
0
29 May 2023
Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice
Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice
Toshinori Kitamura
Tadashi Kozuno
Yunhao Tang
Nino Vieillard
Michal Valko
...
Olivier Pietquin
M. Geist
Csaba Szepesvári
Wataru Kumagai
Yutaka Matsuo
OffRL
30
2
0
22 May 2023
Optimistic Natural Policy Gradient: a Simple Efficient Policy Optimization Framework for Online RL
Optimistic Natural Policy Gradient: a Simple Efficient Policy Optimization Framework for Online RL
Qinghua Liu
Gellert Weisz
András Gyorgy
Chi Jin
Csaba Szepesvári
OffRL
21
8
0
18 May 2023
A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes
A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes
Han Zhong
Tong Zhang
32
26
0
15 May 2023
Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs
Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs
Kaixuan Ji
Qingyue Zhao
Jiafan He
Weitong Zhang
Q. Gu
47
4
0
15 May 2023
Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation
Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation
Yifei Min
Jiafan He
Tianhao Wang
Quanquan Gu
38
7
0
10 May 2023
Optimal Horizon-Free Reward-Free Exploration for Linear Mixture MDPs
Optimal Horizon-Free Reward-Free Exploration for Linear Mixture MDPs
Junkai Zhang
Weitong Zhang
Quanquan Gu
30
3
0
17 Mar 2023
Variance-aware robust reinforcement learning with linear function approximation under heavy-tailed rewards
Variance-aware robust reinforcement learning with linear function approximation under heavy-tailed rewards
Xiang Li
Qiang Sun
24
8
0
09 Mar 2023
Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency
Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency
Heyang Zhao
Jiafan He
Dongruo Zhou
Tong Zhang
Quanquan Gu
24
27
0
21 Feb 2023
Improved Regret Bounds for Linear Adversarial MDPs via Linear Optimization
Improved Regret Bounds for Linear Adversarial MDPs via Linear Optimization
Fang-yuan Kong
Xiangcheng Zhang
Baoxiang Wang
Shuai Li
13
12
0
14 Feb 2023
Nearly Minimax Optimal Reinforcement Learning with Linear Function Approximation
Nearly Minimax Optimal Reinforcement Learning with Linear Function Approximation
Pihe Hu
Yu Chen
Longbo Huang
6
34
0
23 Jun 2022
Computationally Efficient Horizon-Free Reinforcement Learning for Linear Mixture MDPs
Computationally Efficient Horizon-Free Reinforcement Learning for Linear Mixture MDPs
Dongruo Zhou
Quanquan Gu
73
43
0
23 May 2022
Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions
Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions
Jiafan He
Dongruo Zhou
Tong Zhang
Quanquan Gu
63
46
0
13 May 2022
Improved Variance-Aware Confidence Sets for Linear Bandits and Linear Mixture MDP
Improved Variance-Aware Confidence Sets for Linear Bandits and Linear Mixture MDP
Zihan Zhang
Jiaqi Yang
Xiangyang Ji
S. Du
63
36
0
29 Jan 2021
Provably Efficient Reinforcement Learning with Linear Function Approximation Under Adaptivity Constraints
Provably Efficient Reinforcement Learning with Linear Function Approximation Under Adaptivity Constraints
Chi Jin
Zhuoran Yang
Zhaoran Wang
OffRL
120
166
0
06 Jan 2021
Optimism in Reinforcement Learning with Generalized Linear Function Approximation
Optimism in Reinforcement Learning with Generalized Linear Function Approximation
Yining Wang
Ruosong Wang
S. Du
A. Krishnamurthy
132
135
0
09 Dec 2019