报告人：袁晓明
报告地点：数学与统计学院501教室
报告时间：2012年05月18日（星期五）16:30-17:30
邀请人：
报告摘要：
There appear growing interests in applying advanced optimization methods to solve large-scale statistical decision problems. In this talk, I will focus on some splitting methods originated from the classical augmented Lagrangian method for solving some interesting statistical problems such as Lasso, group Lasso, Dantzig selector, sparse covariance selection problem, robust principal component analysis, correlation matrix calibration problems.
主讲人简介：
Dr. Xiaoming Yuan was educated at Nanjing University (B.Sc, M.Phil) and City University of Hong Kong (Ph.D), all majoring in Mathematics. He had worked at University of Victoria, Shanghai Jiao Tong University and University of British Columbia Okanagan before he joined Hong Kong Baptist University. Currently, he is an assistant professor at Department of Mathematics of Hong Kong Baptist University. His research focus is numerical optimization including such topics as variational inequalities and complementarity problems, sparse and low-rank optimization, and first-order methods for large-scale convex programming problems. He is also interested in applications arising in image processing, statistics and operations management.
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