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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

28 January 2024
R. Srikant
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Papers citing "Rates of Convergence in the Central Limit Theorem for Markov Chains, with an Application to TD Learning"

4 / 4 papers shown
Title
Does Worst-Performing Agent Lead the Pack? Analyzing Agent Dynamics in
  Unified Distributed SGD
Does Worst-Performing Agent Lead the Pack? Analyzing Agent Dynamics in Unified Distributed SGD
Jie Hu
Yi-Ting Ma
Do Young Eun
FedML
22
0
0
26 Sep 2024
Gaussian Approximation and Multiplier Bootstrap for Polyak-Ruppert Averaged Linear Stochastic Approximation with Applications to TD Learning
Gaussian Approximation and Multiplier Bootstrap for Polyak-Ruppert Averaged Linear Stochastic Approximation with Applications to TD Learning
S. Samsonov
Eric Moulines
Qi-Man Shao
Zhuo-Song Zhang
Alexey Naumov
25
4
0
26 May 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
28
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
37
11
0
31 Dec 2023
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