Convergence of Stochastic Approximation via Martingale and Converse Lyapunov Methods

3 May 2022

Papers citing "Convergence of Stochastic Approximation via Martingale and Converse Lyapunov Methods"

7 / 7 papers shown

Title
Does Worst-Performing Agent Lead the Pack? Analyzing Agent Dynamics in Unified Distributed SGD Jie Hu Yi-Ting Ma Do Young Eun FedML 29 0 0 26 Sep 2024
Convergence Rates for Stochastic Approximation: Biased Noise with Unbounded Variance, and Applications Rajeeva Laxman Karandikar M. Vidyasagar 25 8 0 05 Dec 2023
A Tutorial Introduction to Reinforcement Learning M. Vidyasagar 11 6 0 03 Apr 2023
Why Target Networks Stabilise Temporal Difference Methods Matt Fellows Matthew Smith Shimon Whiteson OOD AAML 21 7 0 24 Feb 2023
Convergence of Batch Updating Methods with Approximate Gradients and/or Noisy Measurements: Theory and Computational Results Tadipatri Uday M. Vidyasagar 23 0 0 12 Sep 2022
The ODE Method for Asymptotic Statistics in Stochastic Approximation and Reinforcement Learning Vivek Borkar Shuhang Chen Adithya M. Devraj Ioannis Kontoyiannis Sean P. Meyn 16 31 0 27 Oct 2021
Convergence of Batch Asynchronous Stochastic Approximation With Applications to Reinforcement Learning Rajeeva Laxman Karandikar M. Vidyasagar 21 0 0 08 Sep 2021