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$\sqrt{n}$-Regret for Learning in Markov Decision Processes with
  Function Approximation and Low Bellman Rank

n\sqrt{n}n​-Regret for Learning in Markov Decision Processes with Function Approximation and Low Bellman Rank

5 September 2019
Kefan Dong
Jian-wei Peng
Yining Wang
Yuanshuo Zhou
    OffRL
ArXivPDFHTML

Papers citing "$\sqrt{n}$-Regret for Learning in Markov Decision Processes with Function Approximation and Low Bellman Rank"

13 / 13 papers shown
Title
The Effective Horizon Explains Deep RL Performance in Stochastic
  Environments
The Effective Horizon Explains Deep RL Performance in Stochastic Environments
Cassidy Laidlaw
Banghua Zhu
Stuart J. Russell
Anca Dragan
41
2
0
13 Dec 2023
Provably Efficient Reinforcement Learning via Surprise Bound
Provably Efficient Reinforcement Learning via Surprise Bound
Hanlin Zhu
Ruosong Wang
Jason D. Lee
OffRL
28
5
0
22 Feb 2023
Improved Regret for Efficient Online Reinforcement Learning with Linear
  Function Approximation
Improved Regret for Efficient Online Reinforcement Learning with Linear Function Approximation
Uri Sherman
Tomer Koren
Yishay Mansour
34
12
0
30 Jan 2023
Provably Efficient Kernelized Q-Learning
Provably Efficient Kernelized Q-Learning
Shuang Liu
H. Su
MLT
29
4
0
21 Apr 2022
Exponential Family Model-Based Reinforcement Learning via Score Matching
Exponential Family Model-Based Reinforcement Learning via Score Matching
Gen Li
Junbo Li
Anmol Kabra
Nathan Srebro
Zhaoran Wang
Zhuoran Yang
37
4
0
28 Dec 2021
The Power of Exploiter: Provable Multi-Agent RL in Large State Spaces
The Power of Exploiter: Provable Multi-Agent RL in Large State Spaces
Chi Jin
Qinghua Liu
Tiancheng Yu
26
50
0
07 Jun 2021
Online Learning for Unknown Partially Observable MDPs
Online Learning for Unknown Partially Observable MDPs
Mehdi Jafarnia-Jahromi
Rahul Jain
A. Nayyar
34
20
0
25 Feb 2021
Bellman Eluder Dimension: New Rich Classes of RL Problems, and
  Sample-Efficient Algorithms
Bellman Eluder Dimension: New Rich Classes of RL Problems, and Sample-Efficient Algorithms
Chi Jin
Qinghua Liu
Sobhan Miryoosefi
OffRL
38
215
0
01 Feb 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
71
38
0
29 Jan 2021
On Function Approximation in Reinforcement Learning: Optimism in the
  Face of Large State Spaces
On Function Approximation in Reinforcement Learning: Optimism in the Face of Large State Spaces
Zhuoran Yang
Chi Jin
Zhaoran Wang
Mengdi Wang
Michael I. Jordan
41
18
0
09 Nov 2020
FLAMBE: Structural Complexity and Representation Learning of Low Rank
  MDPs
FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs
Alekh Agarwal
Sham Kakade
A. Krishnamurthy
Wen Sun
OffRL
41
223
0
18 Jun 2020
Reinforcement Learning with General Value Function Approximation:
  Provably Efficient Approach via Bounded Eluder Dimension
Reinforcement Learning with General Value Function Approximation: Provably Efficient Approach via Bounded Eluder Dimension
Ruosong Wang
Ruslan Salakhutdinov
Lin F. Yang
23
55
0
21 May 2020
Learning Zero-Sum Simultaneous-Move Markov Games Using Function
  Approximation and Correlated Equilibrium
Learning Zero-Sum Simultaneous-Move Markov Games Using Function Approximation and Correlated Equilibrium
Qiaomin Xie
Yudong Chen
Zhaoran Wang
Zhuoran Yang
41
124
0
17 Feb 2020
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