Speaker: Professor Tingwen Huang
Title: Theory and Applications of Distributed Optimization Based on Stochastic Gradient
Time: 14:30-15:30, April 13th, 2023 (Thursday)
Website: Teams Link
Abstract:
First, the research background on distributed optimization is presented. This includes introductions on some optimization models and applications to smart grid, transportation networks, the reasons for using distributed optimization. Then, overview of the current study status on distributed optimization is presented. This contains the brief introduction on various algorithms in dealing the underlying directed or undirected graphs with different convergent rates. Finally, our recent work on distributed optimization based on the stochastic gradient are presented. The new results include: the expectation of each node can converge to the optimal solution, the range for step sizes can be determined, linear convergent rate can be reached.
Personal Introduction:
Tingwen Huang is a Professor at Texas A&M University at Qatar. He received his B.S. degree from Southwest University, China, 1990, his M.S. degree from Sichuan University, China, 1993, and his Ph.D. degree from Texas A&M University, College Station, Texas, 2002. After graduated from Texas A&M University, he worked as a Visiting Assistant Professor there. Then he joined Texas A&M University at Qatar as an Assistant Professor in August 2003, then he was promoted to Professor in 2013. Dr. Huang’s research areas include neural networks, chaotic dynamical systems, complex networks, optimization and control, smart grid. He was conferred Best Research Project Award by Qatar National Research Fund in 2015, Outstanding Achievement Award by Asia Pacific Neural Networks Society in 2022, The Association of Former Students Distinguished Achievement Award for Research, the highest honor bestowed to a faculty by Texas A&M University in 2022. He a Fellow of IEEE and IAPR.
[Editor:Xiaohan Liu]