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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

21 February 2023
Heyang Zhao
Jiafan He
Dongruo Zhou
Tong Zhang
Quanquan Gu
ArXivPDFHTML

Papers citing "Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency"

15 / 15 papers shown
Title
Improved Regret Analysis in Gaussian Process Bandits: Optimality for Noiseless Reward, RKHS norm, and Non-Stationary Variance
S. Iwazaki
Shion Takeno
76
1
0
10 Feb 2025
Variance-Aware Linear UCB with Deep Representation for Neural Contextual Bandits
Variance-Aware Linear UCB with Deep Representation for Neural Contextual Bandits
H. Bui
Enrique Mallada
Anqi Liu
103
0
0
08 Nov 2024
Gap-Dependent Bounds for Q-Learning using Reference-Advantage Decomposition
Gap-Dependent Bounds for Q-Learning using Reference-Advantage Decomposition
Zhong Zheng
Haochen Zhang
Lingzhou Xue
OffRL
70
2
0
10 Oct 2024
Second Order Bounds for Contextual Bandits with Function Approximation
Second Order Bounds for Contextual Bandits with Function Approximation
Aldo Pacchiano
56
4
0
24 Sep 2024
Variance-Dependent Regret Bounds for Non-stationary Linear Bandits
Variance-Dependent Regret Bounds for Non-stationary Linear Bandits
Zhiyong Wang
Jize Xie
Yi Chen
J. C. Lui
Dongruo Zhou
28
0
0
15 Mar 2024
Reinforcement Learning from Human Feedback with Active Queries
Reinforcement Learning from Human Feedback with Active Queries
Kaixuan Ji
Jiafan He
Quanquan Gu
24
17
0
14 Feb 2024
Settling the Sample Complexity of Online Reinforcement Learning
Settling the Sample Complexity of Online Reinforcement Learning
Zihan Zhang
Yuxin Chen
Jason D. Lee
S. Du
OffRL
95
21
0
25 Jul 2023
Sharp Variance-Dependent Bounds in Reinforcement Learning: Best of Both
  Worlds in Stochastic and Deterministic Environments
Sharp Variance-Dependent Bounds in Reinforcement Learning: Best of Both Worlds in Stochastic and Deterministic Environments
Runlong Zhou
Zihan Zhang
S. Du
44
10
0
31 Jan 2023
Computationally Efficient Horizon-Free Reinforcement Learning for Linear
  Mixture MDPs
Computationally Efficient Horizon-Free Reinforcement Learning for Linear Mixture MDPs
Dongruo Zhou
Quanquan Gu
75
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
66
46
0
13 May 2022
First-Order Regret in Reinforcement Learning with Linear Function
  Approximation: A Robust Estimation Approach
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
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
65
36
0
29 Jan 2021
The Elliptical Potential Lemma Revisited
The Elliptical Potential Lemma Revisited
Alexandra Carpentier
Claire Vernade
Yasin Abbasi-Yadkori
111
20
0
20 Oct 2020
Reward-Free Exploration for Reinforcement Learning
Reward-Free Exploration for Reinforcement Learning
Chi Jin
A. Krishnamurthy
Max Simchowitz
Tiancheng Yu
OffRL
112
194
0
07 Feb 2020
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
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