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Sample-Efficient Reinforcement Learning for Linearly-Parameterized MDPs
  with a Generative Model

Sample-Efficient Reinforcement Learning for Linearly-Parameterized MDPs with a Generative Model

28 May 2021
Bingyan Wang
Yuling Yan
Jianqing Fan
ArXivPDFHTML

Papers citing "Sample-Efficient Reinforcement Learning for Linearly-Parameterized MDPs with a Generative Model"

15 / 15 papers shown
Title
Logarithmic Regret for Reinforcement Learning with Linear Function
  Approximation
Logarithmic Regret for Reinforcement Learning with Linear Function Approximation
Jiafan He
Dongruo Zhou
Quanquan Gu
49
93
0
23 Nov 2020
Efficient Planning in Large MDPs with Weak Linear Function Approximation
Efficient Planning in Large MDPs with Weak Linear Function Approximation
R. Shariff
Csaba Szepesvári
49
22
0
13 Jul 2020
Provably Efficient Reinforcement Learning for Discounted MDPs with
  Feature Mapping
Provably Efficient Reinforcement Learning for Discounted MDPs with Feature Mapping
Dongruo Zhou
Jiafan He
Quanquan Gu
55
135
0
23 Jun 2020
Breaking the Sample Size Barrier in Model-Based Reinforcement Learning
  with a Generative Model
Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model
Gen Li
Yuting Wei
Yuejie Chi
Yuxin Chen
94
128
0
26 May 2020
Deep Reinforcement Learning for Autonomous Driving: A Survey
Deep Reinforcement Learning for Autonomous Driving: A Survey
B. R. Kiran
Ibrahim Sobh
V. Talpaert
Patrick Mannion
A. A. Sallab
S. Yogamani
P. Pérez
327
1,681
0
02 Feb 2020
A Finite-Time Analysis of Q-Learning with Neural Network Function
  Approximation
A Finite-Time Analysis of Q-Learning with Neural Network Function Approximation
Pan Xu
Quanquan Gu
63
67
0
10 Dec 2019
Provably Efficient Reinforcement Learning with Linear Function
  Approximation
Provably Efficient Reinforcement Learning with Linear Function Approximation
Chi Jin
Zhuoran Yang
Zhaoran Wang
Michael I. Jordan
86
556
0
11 Jul 2019
Model-Based Reinforcement Learning with a Generative Model is Minimax
  Optimal
Model-Based Reinforcement Learning with a Generative Model is Minimax Optimal
Alekh Agarwal
Sham Kakade
Lin F. Yang
OffRL
81
171
0
10 Jun 2019
Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and
  Regret Bound
Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound
Lin F. Yang
Mengdi Wang
OffRL
GP
55
286
0
24 May 2019
Stochastic approximation with cone-contractive operators: Sharp
  $\ell_\infty$-bounds for $Q$-learning
Stochastic approximation with cone-contractive operators: Sharp ℓ∞\ell_\inftyℓ∞​-bounds for QQQ-learning
Martin J. Wainwright
43
105
0
15 May 2019
Noisy Matrix Completion: Understanding Statistical Guarantees for Convex
  Relaxation via Nonconvex Optimization
Noisy Matrix Completion: Understanding Statistical Guarantees for Convex Relaxation via Nonconvex Optimization
Yuxin Chen
Yuejie Chi
Jianqing Fan
Cong Ma
Yuling Yan
46
128
0
20 Feb 2019
State Aggregation Learning from Markov Transition Data
State Aggregation Learning from Markov Transition Data
Shiqi Wang
Yizheng Chen
Ahmed Abdou
57
54
0
06 Nov 2018
Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement
  Learning
Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning
Christoph Dann
Tor Lattimore
Emma Brunskill
72
309
0
22 Mar 2017
Efficient Reinforcement Learning in Deterministic Systems with Value
  Function Generalization
Efficient Reinforcement Learning in Deterministic Systems with Value Function Generalization
Zheng Wen
Benjamin Van Roy
55
42
0
18 Jul 2013
Learning Topic Models - Going beyond SVD
Learning Topic Models - Going beyond SVD
Sanjeev Arora
Rong Ge
Ankur Moitra
186
434
0
09 Apr 2012
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