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Concentration of Contractive Stochastic Approximation and Reinforcement
  Learning

Concentration of Contractive Stochastic Approximation and Reinforcement Learning

27 June 2021
Siddharth Chandak
Vivek Borkar
Parth Dodhia
ArXivPDFHTML

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

15 / 15 papers shown
Title
$O(1/k)$ Finite-Time Bound for Non-Linear Two-Time-Scale Stochastic Approximation
O(1/k)O(1/k)O(1/k) Finite-Time Bound for Non-Linear Two-Time-Scale Stochastic Approximation
Siddharth Chandak
29
0
0
27 Apr 2025
Non-Expansive Mappings in Two-Time-Scale Stochastic Approximation: Finite-Time Analysis
Non-Expansive Mappings in Two-Time-Scale Stochastic Approximation: Finite-Time Analysis
Siddharth Chandak
50
1
0
18 Jan 2025
Computing the Bias of Constant-step Stochastic Approximation with
  Markovian Noise
Computing the Bias of Constant-step Stochastic Approximation with Markovian Noise
Sebastian Allmeier
Nicolas Gast
41
5
0
23 May 2024
Constant Stepsize Q-learning: Distributional Convergence, Bias and
  Extrapolation
Constant Stepsize Q-learning: Distributional Convergence, Bias and Extrapolation
Yixuan Zhang
Qiaomin Xie
35
4
0
25 Jan 2024
Full Gradient Deep Reinforcement Learning for Average-Reward Criterion
Full Gradient Deep Reinforcement Learning for Average-Reward Criterion
Tejas Pagare
Vivek Borkar
Konstantin Avrachenkov
26
4
0
07 Apr 2023
Concentration of Contractive Stochastic Approximation: Additive and
  Multiplicative Noise
Concentration of Contractive Stochastic Approximation: Additive and Multiplicative Noise
Zaiwei Chen
S. T. Maguluri
Martin Zubeldia
22
6
0
28 Mar 2023
Equilibrium Bandits: Learning Optimal Equilibria of Unknown Dynamics
Equilibrium Bandits: Learning Optimal Equilibria of Unknown Dynamics
Siddharth Chandak
Ilai Bistritz
Nicholas Bambos
20
4
0
27 Feb 2023
Reinforcement Learning in Non-Markovian Environments
Reinforcement Learning in Non-Markovian Environments
Siddharth Chandak
Pratik Shah
Vivek Borkar
Parth Dodhia
OOD
22
7
0
03 Nov 2022
A Concentration Bound for Distributed Stochastic Approximation
A Concentration Bound for Distributed Stochastic Approximation
H. Dolhare
Vivek Borkar
19
0
0
09 Oct 2022
Bias and Extrapolation in Markovian Linear Stochastic Approximation with
  Constant Stepsizes
Bias and Extrapolation in Markovian Linear Stochastic Approximation with Constant Stepsizes
D. Huo
Yudong Chen
Qiaomin Xie
26
17
0
03 Oct 2022
Concentration bounds for SSP Q-learning for average cost MDPs
Concentration bounds for SSP Q-learning for average cost MDPs
Shaan ul Haque
Vivek Borkar
22
0
0
07 Jun 2022
Target Network and Truncation Overcome The Deadly Triad in $Q$-Learning
Target Network and Truncation Overcome The Deadly Triad in QQQ-Learning
Zaiwei Chen
John-Paul Clarke
S. T. Maguluri
18
19
0
05 Mar 2022
A Concentration Bound for LSPE($λ$)
A Concentration Bound for LSPE(λλλ)
Siddharth Chandak
Vivek Borkar
H. Dolhare
35
0
0
04 Nov 2021
Tight High Probability Bounds for Linear Stochastic Approximation with
  Fixed Stepsize
Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize
Alain Durmus
Eric Moulines
A. Naumov
S. Samsonov
Kevin Scaman
Hoi-To Wai
19
20
0
02 Jun 2021
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
26
28
0
10 Sep 2019
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