activity
20182021
most citedAnalysis of the Optimization Landscape of Linear Quadratic Gaussian (LQG) Control

18 citations · 19 across the 2 of their papers we have counts for

collaborators

5 papers

math.OC202118 cited

Analysis of the Optimization Landscape of Linear Quadratic Gaussian (LQG) Control

Yang Zheng, Yujie Tang, Na Li

This paper revisits the classical Linear Quadratic Gaussian (LQG) control from a modern optimization perspective. We analyze two aspects of the optimization landscape of the LQG pr…

math.OC20201 cited

Zeroth-Order Feedback Optimization for Cooperative Multi-Agent Systems

Yujie Tang, Zhaolin Ren, Na Li

We study a class of cooperative multi-agent optimization problems, where each agent is associated with a local action vector and a local cost, and the goal is to cooperatively find…

eess.SY2019

Distributed Reinforcement Learning for Decentralized Linear Quadratic Control: A Derivative-Free Policy Optimization Approach

Yingying Li, Yujie Tang, Runyu Zhang +1

This paper considers a distributed reinforcement learning problem for decentralized linear quadratic control with partial state observations and local costs. We propose a Zero-Orde…

math.OC2019

Distributed Zero-Order Algorithms for Nonconvex Multi-Agent Optimization

Yujie Tang, Junshan Zhang, Na Li

Distributed multi-agent optimization finds many applications in distributed learning, control, estimation, etc. Most existing algorithms assume knowledge of first-order information…

math.OC2018

Running Primal-Dual Gradient Method for Time-Varying Nonconvex Problems

Yujie Tang, Emiliano Dall'Anese, Andrey Bernstein +1

This paper considers a nonconvex optimization problem that evolves over time, and addresses the synthesis and analysis of regularized primal-dual gradient methods to track a Karush…