422 citations · 550 across the 13 of their papers we have counts for
9 papers · 1 filter
On the Global Optimality of Direct Policy Search for Nonsmooth Output-Feedback Control
Yujie Tang, Yang Zheng
Direct policy search has achieved great empirical success in reinforcement learning. Recently, there has been increasing interest in studying its theoretical properties for continu…
Escaping saddle points in zeroth-order optimization: the power of two-point estimators
Zhaolin Ren, Yujie Tang, Na Li
Two-point zeroth order methods are important in many applications of zeroth-order optimization, such as robotics, wind farms, power systems, online optimization, and adversarial ro…
Communication-Efficient Distributed SGD with Compressed Sensing
Yujie Tang, Vikram Ramanathan, Junshan Zhang +1
We consider large scale distributed optimization over a set of edge devices connected to a central server, where the limited communication bandwidth between the server and edge dev…
Improve Single-Point Zeroth-Order Optimization Using High-Pass and Low-Pass Filters
Xin Chen, Yujie Tang, Na Li
Single-point zeroth-order optimization (SZO) is useful in solving online black-box optimization and control problems in time-varying environments, as it queries the function value…
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…
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…
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…
Semi-Global Exponential Stability of Augmented Primal-Dual Gradient Dynamics for Constrained Convex Optimization
Yujie Tang, Guannan Qu, Na Li
Primal-dual gradient dynamics that find saddle points of a Lagrangian have been widely employed for handling constrained optimization problems. Building on existing methods, we ext…
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…