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Finite-Time Performance Bounds and Adaptive Learning Rate Selection for
  Two Time-Scale Reinforcement Learning

Finite-Time Performance Bounds and Adaptive Learning Rate Selection for Two Time-Scale Reinforcement Learning

14 July 2019
Harsh Gupta
R. Srikant
Lei Ying
ArXivPDFHTML

Papers citing "Finite-Time Performance Bounds and Adaptive Learning Rate Selection for Two Time-Scale Reinforcement Learning"

31 / 31 papers shown
Title
Fast Two-Time-Scale Stochastic Gradient Method with Applications in Reinforcement Learning
Fast Two-Time-Scale Stochastic Gradient Method with Applications in Reinforcement Learning
Sihan Zeng
Thinh T. Doan
56
5
0
15 May 2024
Rates of Convergence in the Central Limit Theorem for Markov Chains, with an Application to TD Learning
Rates of Convergence in the Central Limit Theorem for Markov Chains, with an Application to TD Learning
R. Srikant
46
5
0
28 Jan 2024
Central Limit Theorem for Two-Timescale Stochastic Approximation with
  Markovian Noise: Theory and Applications
Central Limit Theorem for Two-Timescale Stochastic Approximation with Markovian Noise: Theory and Applications
Jie Hu
Vishwaraj Doshi
Do Young Eun
38
4
0
17 Jan 2024
Tight Finite Time Bounds of Two-Time-Scale Linear Stochastic Approximation with Markovian Noise
Tight Finite Time Bounds of Two-Time-Scale Linear Stochastic Approximation with Markovian Noise
Shaan ul Haque
S. Khodadadian
S. T. Maguluri
44
11
0
31 Dec 2023
Finite-Time Analysis of Whittle Index based Q-Learning for Restless
  Multi-Armed Bandits with Neural Network Function Approximation
Finite-Time Analysis of Whittle Index based Q-Learning for Restless Multi-Armed Bandits with Neural Network Function Approximation
Guojun Xiong
Jian Li
38
13
0
03 Oct 2023
High-probability sample complexities for policy evaluation with linear
  function approximation
High-probability sample complexities for policy evaluation with linear function approximation
Gen Li
Weichen Wu
Yuejie Chi
Cong Ma
Alessandro Rinaldo
Yuting Wei
OffRL
35
7
0
30 May 2023
Intelligent gradient amplification for deep neural networks
Intelligent gradient amplification for deep neural networks
S. Basodi
K. Pusuluri
Xueli Xiao
Yi Pan
ODL
21
1
0
29 May 2023
Finite-Time Error Bounds for Greedy-GQ
Finite-Time Error Bounds for Greedy-GQ
Yue Wang
Yi Zhou
Shaofeng Zou
34
1
0
06 Sep 2022
A Single-Timescale Analysis For Stochastic Approximation With Multiple
  Coupled Sequences
A Single-Timescale Analysis For Stochastic Approximation With Multiple Coupled Sequences
Han Shen
Tianyi Chen
54
15
0
21 Jun 2022
Stochastic Gradient Descent with Dependent Data for Offline
  Reinforcement Learning
Stochastic Gradient Descent with Dependent Data for Offline Reinforcement Learning
Jing-rong Dong
Xin T. Tong
OffRL
35
2
0
06 Feb 2022
Convergence Rates of Two-Time-Scale Gradient Descent-Ascent Dynamics for
  Solving Nonconvex Min-Max Problems
Convergence Rates of Two-Time-Scale Gradient Descent-Ascent Dynamics for Solving Nonconvex Min-Max Problems
Thinh T. Doan
22
15
0
17 Dec 2021
Finite-Time Error Bounds for Distributed Linear Stochastic Approximation
Finite-Time Error Bounds for Distributed Linear Stochastic Approximation
Yixuan Lin
V. Gupta
Ji Liu
32
3
0
24 Nov 2021
Gradient Temporal Difference with Momentum: Stability and Convergence
Gradient Temporal Difference with Momentum: Stability and Convergence
Rohan Deb
S. Bhatnagar
19
5
0
22 Nov 2021
Finite-Time Complexity of Online Primal-Dual Natural Actor-Critic
  Algorithm for Constrained Markov Decision Processes
Finite-Time Complexity of Online Primal-Dual Natural Actor-Critic Algorithm for Constrained Markov Decision Processes
Sihan Zeng
Thinh T. Doan
Justin Romberg
102
17
0
21 Oct 2021
PER-ETD: A Polynomially Efficient Emphatic Temporal Difference Learning
  Method
PER-ETD: A Polynomially Efficient Emphatic Temporal Difference Learning Method
Ziwei Guan
Tengyu Xu
Yingbin Liang
26
4
0
13 Oct 2021
A Two-Time-Scale Stochastic Optimization Framework with Applications in
  Control and Reinforcement Learning
A Two-Time-Scale Stochastic Optimization Framework with Applications in Control and Reinforcement Learning
Sihan Zeng
Thinh T. Doan
Justin Romberg
67
22
0
29 Sep 2021
Online Robust Reinforcement Learning with Model Uncertainty
Online Robust Reinforcement Learning with Model Uncertainty
Yue Wang
Shaofeng Zou
OOD
OffRL
76
97
0
29 Sep 2021
A Credibility-aware Swarm-Federated Deep Learning Framework in Internet
  of Vehicles
A Credibility-aware Swarm-Federated Deep Learning Framework in Internet of Vehicles
Zhe Wang
Xinhang Li
Tianhao Wu
Chen Xu
Lin Zhang
FedML
30
15
0
09 Aug 2021
Online Bootstrap Inference For Policy Evaluation in Reinforcement
  Learning
Online Bootstrap Inference For Policy Evaluation in Reinforcement Learning
Pratik Ramprasad
Yuantong Li
Zhuoran Yang
Zhaoran Wang
W. Sun
Guang Cheng
OffRL
50
27
0
08 Aug 2021
Analysis of a Target-Based Actor-Critic Algorithm with Linear Function
  Approximation
Analysis of a Target-Based Actor-Critic Algorithm with Linear Function Approximation
Anas Barakat
Pascal Bianchi
Julien Lehmann
32
9
0
14 Jun 2021
Finite-Time Convergence Rates of Nonlinear Two-Time-Scale Stochastic
  Approximation under Markovian Noise
Finite-Time Convergence Rates of Nonlinear Two-Time-Scale Stochastic Approximation under Markovian Noise
Thinh T. Doan
18
15
0
04 Apr 2021
Greedy-GQ with Variance Reduction: Finite-time Analysis and Improved
  Complexity
Greedy-GQ with Variance Reduction: Finite-time Analysis and Improved Complexity
Shaocong Ma
Ziyi Chen
Yi Zhou
Shaofeng Zou
17
11
0
30 Mar 2021
Is Q-Learning Minimax Optimal? A Tight Sample Complexity Analysis
Is Q-Learning Minimax Optimal? A Tight Sample Complexity Analysis
Gen Li
Changxiao Cai
Ee
Yuting Wei
Yuejie Chi
OffRL
55
75
0
12 Feb 2021
On the Stability of Random Matrix Product with Markovian Noise:
  Application to Linear Stochastic Approximation and TD Learning
On the Stability of Random Matrix Product with Markovian Noise: Application to Linear Stochastic Approximation and TD Learning
Alain Durmus
Eric Moulines
A. Naumov
S. Samsonov
Hoi-To Wai
29
19
0
30 Jan 2021
Nonlinear Two-Time-Scale Stochastic Approximation: Convergence and
  Finite-Time Performance
Nonlinear Two-Time-Scale Stochastic Approximation: Convergence and Finite-Time Performance
Thinh T. Doan
14
45
0
03 Nov 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
34
125
0
26 May 2020
Non-asymptotic Convergence Analysis of Two Time-scale (Natural)
  Actor-Critic Algorithms
Non-asymptotic Convergence Analysis of Two Time-scale (Natural) Actor-Critic Algorithms
Tengyu Xu
Zhe Wang
Yingbin Liang
26
57
0
07 May 2020
A Finite Time Analysis of Two Time-Scale Actor Critic Methods
A Finite Time Analysis of Two Time-Scale Actor Critic Methods
Yue Wu
Weitong Zhang
Pan Xu
Quanquan Gu
90
146
0
04 May 2020
Finite-Time Analysis and Restarting Scheme for Linear Two-Time-Scale
  Stochastic Approximation
Finite-Time Analysis and Restarting Scheme for Linear Two-Time-Scale Stochastic Approximation
Thinh T. Doan
21
36
0
23 Dec 2019
A Multistep Lyapunov Approach for Finite-Time Analysis of Biased
  Stochastic Approximation
A Multistep Lyapunov Approach for Finite-Time Analysis of Biased Stochastic Approximation
Gang Wang
Bingcong Li
G. Giannakis
31
28
0
10 Sep 2019
Finite-Sample Analysis for SARSA with Linear Function Approximation
Finite-Sample Analysis for SARSA with Linear Function Approximation
Shaofeng Zou
Tengyu Xu
Yingbin Liang
32
146
0
06 Feb 2019
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