Matrix optimization in data science
报告题目(Title)：Matrix optimization in data science
报告人(Speaker)：丁超（中国科学院应用数学研究所）
地点(Place)：后主楼1124
时间(Time)：12月18日（星期五），15:00-16:00
邀请人(Inviter)：蔡勇勇
报告摘要
In this talk, I will briefly introduce a class of optimization problems, so-called matrix optimization problems (MOPs). The MOP has been recognized in recent years to be a powerful tool by researchers far beyond the optimization community to model many important applications. This trend can be credited to some extent to the exciting developments in the emerging field of data science. I will present some recent progress on applications of MOPs in data analytics.
主讲人简介
Dr. Chao Ding is an associate professor of Institute of Applied Mathematics, Academy of Mathematics and Systems Science, Chinese Academy of Sciences. He received a PhD in mathematics from National University of Singapore in 2012. His research interest includes matrix optimization, MPEC and machine learning. His work has been published in many leading journals such as Mathematical Programming and SIAM Journal on optimization.
