云南大学唐年胜教授学术报告 3月16日上午
发布时间: 2019-03-15 访问次数: 13

报告题目【Category-Adaptive Variable Screening for Ultra-high Dimensional Heterogeneous Categorical Data】

时间:2019年3月16日 (星期六)上午 9:00 

地点:旗山校区理工北楼601报告厅

主讲:云南大学教授,唐年胜

主办:数学与信息学院

参加对象:相关教师和研究生


专家简介:唐年胜,云南大学二级教授、数学与统计学院院长、博士生导师。2007年入选教育部新世纪优秀人才支持计划;2012年获国家杰出青年科学基金、“云南省中青年学术和技术带头人”称号;2013年入选教育部“长江学者”奖励计划特聘教授、享受省政府特殊津贴;2014年获云南省有突出贡献优秀专业技术人才二等奖、入选云南省首批“云岭学者”和“省委联系专家”;2015年入选云南省高等学校教学名师、云南省科技领军人才、国家百千万人才工程,获“国家有突出贡献中青年专家”荣誉称号;2016年12月当选为Elected ISI Member(国际统计学会推选会员);2016年享受国务院政府特殊津贴;2017年当选国际泛华统计学会“Board of Directors”;2018年获ICSA Outstanding Service Award。在国内外学术刊物发表论文153余篇,其中SCI检索121篇。曾获“霍英东教育基金会第九届高等院校青年教师奖”,云南省自然科学二等奖2项、三等奖1项;国家统计局全国统计科研优秀成果二等奖6项。


报告摘要:The populations of interest in modern studies are very often heterogeneous. The population heterogeneity, the qualitative nature of the outcome variable and the high dimensionality of the predictors pose significant challenge in statistical analysis. In this article, we introduce a category-adaptive screening procedure with high-dimensional heterogeneous data, which is to detect category-specific important covariates. The proposal is a model-free approach without any specification of a regression model and an adaptive procedure in the sense that the set of active variables is allowed to vary across different categories, thus making it more flexible to accommodate heterogeneity. For response-selective sampling data, another main discovery of this paper is that  the proposed method works directly without any modification. Under mild regularity conditions, the newly procedure is shown to possess the sure screening and ranking consistency properties. Simulation studies contain supportive evidence  that the proposed method performs well under various settings and it is effective to extract category-specific information. Applications are illustrated with two real data sets.