Speaker: BAO Chenglong, an Assistant Professor at Mathematical Sciences Center, Tsinghua University. He received his undergraduate degree from the Department of Mathematics, Sun Yat-sen University in 2009, and his Ph.D. degree from the Department of Mathematics, National University of Singapore in 2014, and conducted postdoctoral research in the Department of Mathematics, National University of Singapore from 2015 to 2018. His research interests are mainly in the area of models and algorithms for mathematical image processing, and he has published more than 30 academic papers in IEEE TPAMI, SIIMS, SISC, ACHA journals and conferences such as CVPR, ICML, NeurIPS, ICLR.
Venue: Tencent Conference ID: 942-721-395
Abstract: In this talk, I will discuss our recent progress on developing a modified Anderson mixing schemes with short memory requirement for solving linear, nonlinear systems and stochastic programming. The convergence analysis will be reported and extensive numerical results will be present.