Concentration of Contractive Stochastic Approximation and Reinforcement
Learning

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Concentration of Contractive Stochastic Approximation and Reinforcement Learning

27 June 2021

Siddharth Chandak

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Papers citing "Concentration of Contractive Stochastic Approximation and Reinforcement Learning"

14 / 14 papers shown

Title
Non-Expansive Mappings in Two-Time-Scale Stochastic Approximation: Finite-Time Analysis Siddharth Chandak 99 1 0 18 Jan 2025
Is Q-Learning Minimax Optimal? A Tight Sample Complexity Analysis Gen Li Changxiao Cai Ee Yuting Wei Yuejie Chi OffRL 87 77 0 12 Feb 2021
A Lyapunov Theory for Finite-Sample Guarantees of Asynchronous Q-Learning and TD-Learning Variants Zaiwei Chen S. T. Maguluri Sanjay Shakkottai Karthikeyan Shanmugam OffRL 170 55 0 02 Feb 2021
Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction Gen Li Yuting Wei Yuejie Chi Yuantao Gu Yuxin Chen OffRL 142 120 0 04 Jun 2020
Finite-Time Analysis of Stochastic Gradient Descent under Markov Randomness Thinh T. Doan Lam M. Nguyen Nhan H. Pham Justin Romberg 57 22 0 24 Mar 2020
Finite-Time Analysis of Asynchronous Stochastic Approximation and $Q$ -Learning Guannan Qu Adam Wierman 64 110 0 01 Feb 2020
A Multistep Lyapunov Approach for Finite-Time Analysis of Biased Stochastic Approximation Gang Wang Bingcong Li G. Giannakis 85 28 0 10 Sep 2019
Variance-reduced $Q$ -learning is minimax optimal Martin J. Wainwright OffRL 61 93 0 11 Jun 2019
$Stochastic approximation with cone-contractive operators: Sharp $\ell_\infty$-bounds for $Q$-learning$ Stochastic approximation with cone-contractive operators: Sharp $\ell_\infty$ -bounds for $Q$ -learning Martin J. Wainwright 50 105 0 15 May 2019
Finite-Time Error Bounds For Linear Stochastic Approximation and TD Learning R. Srikant Lei Ying 65 252 0 03 Feb 2019
On Markov Chain Gradient Descent Tao Sun Yuejiao Sun W. Yin BDL 46 102 0 12 Sep 2018
Is Q-learning Provably Efficient? Chi Jin Zeyuan Allen-Zhu Sébastien Bubeck Michael I. Jordan OffRL 78 812 0 10 Jul 2018
A Finite Time Analysis of Temporal Difference Learning With Linear Function Approximation Jalaj Bhandari Daniel Russo Raghav Singal 106 340 0 06 Jun 2018
Concentration bounds for temporal difference learning with linear function approximation: The case of batch data and uniform sampling L. A. Prashanth N. Korda Rémi Munos 83 16 0 11 Jun 2013

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