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Finite-time High-probability Bounds for Polyak-Ruppert Averaged Iterates
  of Linear Stochastic Approximation

Finite-time High-probability Bounds for Polyak-Ruppert Averaged Iterates of Linear Stochastic Approximation

10 July 2022
Alain Durmus
Eric Moulines
A. Naumov
S. Samsonov
ArXivPDFHTML

Papers citing "Finite-time High-probability Bounds for Polyak-Ruppert Averaged Iterates of Linear Stochastic Approximation"

10 / 10 papers shown
Title
A note on concentration inequalities for the overlapped batch mean variance estimators for Markov chains
A note on concentration inequalities for the overlapped batch mean variance estimators for Markov chains
Eric Moulines
A. Naumov
S. Samsonov
18
0
0
13 May 2025
Nonasymptotic Analysis of Stochastic Gradient Descent with the Richardson-Romberg Extrapolation
Nonasymptotic Analysis of Stochastic Gradient Descent with the Richardson-Romberg Extrapolation
Marina Sheshukova
Denis Belomestny
Alain Durmus
Eric Moulines
Alexey Naumov
S. Samsonov
41
1
0
07 Oct 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
33
4
0
26 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
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
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
33
7
0
30 May 2023
High-dimensional scaling limits and fluctuations of online least-squares
  SGD with smooth covariance
High-dimensional scaling limits and fluctuations of online least-squares SGD with smooth covariance
Krishnakumar Balasubramanian
Promit Ghosal
Ye He
40
5
0
03 Apr 2023
Statistical Inference for Linear Functionals of Online SGD in High-dimensional Linear Regression
Statistical Inference for Linear Functionals of Online SGD in High-dimensional Linear Regression
Bhavya Agrawalla
Krishnakumar Balasubramanian
Promit Ghosal
27
2
0
20 Feb 2023
Learning from time-dependent streaming data with online stochastic
  algorithms
Learning from time-dependent streaming data with online stochastic algorithms
Antoine Godichon-Baggioni
Nicklas Werge
Olivier Wintenberger
35
3
0
25 May 2022
A Statistical Analysis of Polyak-Ruppert Averaged Q-learning
A Statistical Analysis of Polyak-Ruppert Averaged Q-learning
Xiang Li
Wenhao Yang
Jiadong Liang
Zhihua Zhang
Michael I. Jordan
42
15
0
29 Dec 2021
1