智能无人系统实验室E

Research Seminars

Distributed Gradient Tracking for Optimization in Networks

date:2019-10-29

22864

Bio:

Keyou You received the B.S. degree in Statistical Science from Sun Yat-sen University, Guangzhou, China, in 2007 and the Ph.D. degree in Electrical and Electronic Engineering from Nanyang Technological University (NTU), Singapore, in 2012. After briefly working as a Research Fellow at NTU, he joined Tsinghua University in Beijing, China where he is now a tenured Associate Professor in the Department of Automation. He held visiting positions at Politecnico di Torino, The Hong Kong University of Science and Technology, The University of Melbourne and etc.

His current research interests include networked control systems, distributed algorithms and learning, and their applications. Dr. You received the Guan Zhaozhi award at the 29th Chinese Control Conference in 2010, a CSC-IBM China Faculty Award in 2014, and the ACA Temasek Young Educator Award in 2019. He was selected to the National 1000-Youth Talent Program of China in 2014 and received the National Natural Science Fund for Excellent Young Scholars in 2017.

Abstract:

Many problems of recent interest in control and machine learning can be posed in the framework of mathematical optimization. As data gets larger and more distributed, distributed algorithms over networks provide ample opportunities to improve the speed and accuracy of optimization. In this talk, we shall exploit the distributed gradient tracking technique (DGT) to solve large-scale optimization problems, e.g., the fully Asynchronous DGT which is easy to implement in directed networks with distributed datasets and robust to bounded transmission delays, while maintaining a linear convergence rate in the worst case if local functions are strongly-convex with Lipschitz-continuous gradients. Moreover, we adopt the DGT to design distributed algorithms with explicit convergence rates for the distributed resource allocation and distributed training over networks, respectively. Experiments are included to show their advantages again the-state-of-the-art algorithms.

https://www.westlake.edu.cn/info/1384/3452.htm

时间:2019年11月7日(周四)10:30-11:30AM

Time:10:30-11:30AM, Thursday, November 7, 2019

主持人:工学院PI赵世钰博士

Host: Dr. Shiyu Zhao, School of Engineering

地点:西湖大学云栖校区5号楼一楼学术报告厅

Venue:Lecture Hall, 1st Floor, Building#5, Yunqi Campus