报告题目：Networked Parallel Algorithms for Robust Convex Programs
报告摘要：This talk studies a parallel computing framework to distributedly solve robust convex optimization (RCO) where the constraints are affected by nonlinear uncertainties. We adopt a scenario approach by randomly sampling the uncertainty set, and obtained a scenario problem (SP) with optimality guarantee in a probabilistic sense. To solve the SP, we resort to multiple parallel processors that are distributed among different nodes of a network. Then, we propose a primal-dual sub-gradient algorithm and a random projection algorithm to distributedly solve the SP over undirected and directed graphs, respectively. Both algorithms are given in an explicit recursive form with simple iterations, which are especially suited for processors with limited computational capability. We show that, if the underlying graph is strongly connected, each node asymptotically computes a common optimal solution to the SP with a convergence rate where is a sequence of appropriately decreasing stepsizes.
报告人概况：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, where he is now an Associate Professor in the Department of Automation. He held visiting positions at Politecnico di Torino, Hong Kong University of Science and Technology, University of Melbourne and etc. His current research interests include networked control systems, parallel networked algorithms, and their applications.
Dr. You received the Guan Zhaozhi award at the 29th Chinese Control Conference in 2010, and a CSC-IBM China Faculty Award in 2014. He was selected to the national 1000-Youth Talent Program of China in 2014.