activity
20182021
most citedA Distributed Online Convex Optimization Algorithm with Improved Dynamic Regret

4 citations · 7 across the 4 of their papers we have counts for

collaborators

6 papers

math.OC20211 cited

Asynchronous Zeroth-Order Distributed Optimization with Residual Feedback

Yi Shen, Yan Zhang, Scott Nivison +2

We consider a zeroth-order distributed optimization problem, where the global objective function is a black-box function and, as such, its gradient information is inaccessible to t…

cs.LG20211 cited

Learning without Knowing: Unobserved Context in Continuous Transfer Reinforcement Learning

Chenyu Liu, Yan Zhang, Yi Shen +1

In this paper, we consider a transfer Reinforcement Learning (RL) problem in continuous state and action spaces, under unobserved contextual information. For example, the context c…

math.OC20194 cited

A Distributed Online Convex Optimization Algorithm with Improved Dynamic Regret

Yan Zhang, Robert J. Ravier, Michael M. Zavlanos +1

In this paper, we consider the problem of distributed online convex optimization, where a network of local agents aim to jointly optimize a convex function over a period of multipl…

math.OC2019

Distributed Online Convex Optimization with Improved Dynamic Regret

Yan Zhang, Robert J. Ravier, Vahid Tarokh +1

In this paper, we consider the problem of distributed online convex optimization, where a group of agents collaborate to track the global minimizers of a sum of time-varying object…

cs.LG20191 cited

Distributed off-Policy Actor-Critic Reinforcement Learning with Policy Consensus

Yan Zhang, Michael M. Zavlanos

In this paper, we propose a distributed off-policy actor critic method to solve multi-agent reinforcement learning problems. Specifically, we assume that all agents keep local esti…

math.OC2018

Augmented Lagrangian Optimization under Fixed-Point Arithmetic

Yan Zhang, Michael M. Zavlanos

In this paper, we propose an inexact Augmented Lagrangian Method (ALM) for the optimization of convex and nonsmooth objective functions subject to linear equality constraints and b…