应边伟教授的邀请，受国际合作处资助，西蒙弗雷泽大学吕兆松教授近日来访我校并做学术报告，欢迎感兴趣的师生参加。
讲学时间、地点及题目
1. 时间及地点：2018年8月7日 16:30-18:00 新活动中心216
Title: Algorithmic Development for Computing B-stationary Points of a Class of Nonsmooth DC Programs
2. 时间及地点：2018年8月8日 10:30-12:00 格物楼503
Title: Iteration-Complexity of First-Order Augmented Lagrangian Methods for Convex Conic Programming
3. 时间及地点：2018年8月8日14:20-15:50 格物楼503
Title: A Randomized Nonmonotone Block Proximal Gradient Method for a Class of Structured Nonlinear Programming (I)
4. 时间及地点：2018年8月8日16:00-17:30 格物楼503
Title: A Randomized Nonmonotone Block Proximal Gradient Method for a Class of Structured Nonlinear Programming (II)
专家简介： Dr. Zhaosong Lu is a full Professor of Mathematics and an associate faculty member in Statistics and Actuarial Science at Simon Fraser University. He received PhD in Operations Research from the School of Industrial and Systems Engineering of Georgia Tech in 2005 under the supervision of Dr. Renato Monteiro and Dr. Arkadi Nemirovski. He was a Visiting Assistant Professor of Mathematical Sciences at Carnegie Mellon University during 2005-2006. He was also a Visiting Associate Professor at Texas A&M University and Arizona State University, and a Visiting Researcher at Microsoft Research, Redmond during 2012-2013. His research interests include theory and algorithms for continuous optimization, and applications in data analytics, finance, statistics, machine learning, image processing, engineering design, and decision-making under uncertainty. He was a finalist of INFORMS George Nicholson Prize. He has published numerous papers in major journals of his research areas such as SIAM Journal on Optimization, SIAM Journal on Numerical Analysis, SIAM Journal on Scientific Computing, SIAM Journal on Matrix Analysis and Application, Mathematical Programming, and Mathematics of Operations Research. He also served on INFORMS George Nicholson Prize Committee in 2014 and 2015. Currently, he is an Associate Editor for SIAM Journal on Optimization, Computational Optimization and Applications, and Big Data and Information Analytics.
