6 citations · 19 across the 7 of their papers we have counts for
7 papers
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…
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…
A New One-Point Residual-Feedback Oracle For Black-Box Learning and Control
Yan Zhang, Yi Zhou, Kaiyi Ji +1
Zeroth-order optimization (ZO) algorithms have been recently used to solve black-box or simulation-based learning and control problems, where the gradient of the objective function…
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…
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…
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…
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…