报告题目：Distributed Gradient Tracking for Optimization and Learning over Networks

报告人：游科友副教授

报告时间：2019年12月12日（周四）上午09:30

报告地点：数计学院4号楼229室

报告摘要：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 offer 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 and learning 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 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 against the-state-of-the-art algorithms.

报告人简介：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 an Associate Professor with tenure 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.

欢迎感兴趣的师生参加！