2018年6月4日下午16点在林园校区教学图书楼705室，新加坡南洋理工大学潘光明教授莅临我院做学术报告。报告由学院副院长王纯杰主持，学院副院长徐平峰、学院部分老师、研究生、及本科生和其他学院师生参加了本次学术报告会。

报告题目：Multiple Change Point Detection for Correlated High-Dimensional Observations via the Largest Eigenvalue

摘要：

We propose to deal with a mean vector change point detection problem from a new perspective via the largest eigenvalue when the data dimension p is comparable to the sample size n. An optimization approach is proposed to figure out both the unknown number of change points and multiple change point positions simultaneously. Moreover, an adjustment term is introduced to handle sparse signals when the change only appears in few components out of the p dimensions. The computation time is controlled at $O(n^2)$ by adopting a dynamic programming, regardless of the true number of change points $k_0$. Theoretical results are developed and various simulations are conducted to show the effectiveness of our method.

潘光明 新加坡南洋理工大学，数学系教授。中国科技大学博士毕业，主要研究领域随机矩阵，高维统计推断和变点研究。

本次报告让师生对其报告内容有了形象的了解，开扩了视野，而且进一步激发了广大师生的极大兴趣，在场师生均表示，聆听本次报告受益匪浅，获益良多，增强了自信心，进一步争强了广大师生的统计思维，加强了学生对统计专业的喜爱！

数学与统计学院

2018年6月4日