报告题目：Correlation pursuit and its application in threat detection

报告人：佐治亚大学统计系钟文瑄教授

报告地点：校本部中财大厦二层通用教室三

报告时间：6月11日下午14:00

报告摘要：

In this talk, I will introduce a stepwise procedure, correlation pursuit (COP) for variable selection under the sufficient dimension reduction framework, in which the response variable Y is influenced by a few linear combinations of predictors through an unknown function. Unlike linear stepwise regression, COP does not impose a special form of relationship (such as linear) between the response variable and the predictor variables. The COP procedure selects variables that attain the maximum correlation between the transformed response and the linear combination of the variables. Various asymptotic properties of the COP procedure are established and, in particular, its variable selection performance under a diverging number of predictors and sample size will be discussed. The performance of the COP procedure in comparison with existing methods will be demonstrated using a real data that related to threat detection.

报告人简介：

钟文瑄教授1996年毕业于南开大学，获统计学士学位；2005年获普渡大学统计学博士学位；2005年至2007年在哈佛大学统计系从事博士后研究。2007年至2013年，任伊利诺伊大学香槟分校（UIUC）统计系助理教授；2013年秋，加入佐治亚大学（UGA）统计系，担任副教授至今。钟文瑄教授在高维数据统计分析理论方面有很深入的研究，在生物信息、分析化学等应用方向做出了一系列重要工作。在高水平学术杂志上发表论文20余篇，承担3项美国国家科学基金（NSF）科研项目。