activity
20152026
most citedFinite-Time Analysis of Distributed TD(0) with Linear Function Approximation for Multi-Agent Reinforcement Learning

50 citations · 194 across the 41 of their papers we have counts for

collaborators
Showing 2021 · math.OCShow all

7 papers · 2 filters

math.OC2021

Convergence Rates of Two-Time-Scale Gradient Descent-Ascent Dynamics for Solving Nonconvex Min-Max Problems

Thinh T. Doan

There are much recent interests in solving noncovnex min-max optimization problems due to its broad applications in many areas including machine learning, networked resource alloca…

math.OC2021

Convergence Rates of Decentralized Gradient Methods over Cluster Networks

Amit Dutta, Nila Masrourisaadat, Thinh T. Doan

We present an analysis for the performance of decentralized consensus-based gradient (DCG) methods for solving optimization problems over a cluster network of nodes. This type of n…

math.OC2021★ 1 cited

Finite-Time Complexity of Online Primal-Dual Natural Actor-Critic Algorithm for Constrained Markov Decision Processes

Sihan Zeng, Thinh T. Doan, Justin Romberg

We consider a discounted cost constrained Markov decision process (CMDP) policy optimization problem, in which an agent seeks to maximize a discounted cumulative reward subject to…

math.OC2021★ 2 cited

A Two-Time-Scale Stochastic Optimization Framework with Applications in Control and Reinforcement Learning

Sihan Zeng, Thinh T. Doan, Justin Romberg

We study a new two-time-scale stochastic gradient method for solving optimization problems, where the gradients are computed with the aid of an auxiliary variable under samples gen…

math.OC2021

Distributed Dual Subgradient Methods with Averaging and Applications to Grid Optimization

Subhonmesh Bose, Hoa Dinh Nguyen, Haitian Liu +3

We study finite-time performance of a recently proposed distributed dual subgradient (DDSG) method for convex constrained multi-agent optimization problems. The algorithm enjoys pe…

math.OC2021★ 4 cited

Finite-Time Convergence Rates of Nonlinear Two-Time-Scale Stochastic Approximation under Markovian Noise

Thinh T. Doan

We study the so-called two-time-scale stochastic approximation, a simulation-based approach for finding the roots of two coupled nonlinear operators. Our focus is to characterize i…

math.OC2021

Convergence Rates of Distributed Consensus over Cluster Networks: A Two-Time-Scale Approach

Amit Dutta, Almuatazbellah M. Boker, Thinh T. Doan

We study the popular distributed consensus method over networks composed of a number of densely connected clusters with a sparse connection between them. In these cluster networks,…