时间：2018年10月22日(周一)下午14:30-15:30
地点：中山北路校区理科大楼A1716报告厅
题目：Quantile Regression Under Memory Constraint
报告人：刘卫东上海交通大学自然科学研究院
摘要：
For the etiology, progression, and treatment of complex diseases, gene-environment (G-E) interactions have important implications beyond the main G and E effects. G-E interaction analysis can be more challenging with the higher dimensionality and need for accommodating the “main effects, interactions” hierarchy. In the recent literature, an array of novel methods, many of which are based on the penalization technique, have been developed. In most of these studies, however, the structures of G measurements, for example the adjacency structure of SNPs (attributable to their physical adjacency on the chromosomes) and network structure of gene expressions (attributable to their coordinated biological functions and correlated measurements), have not been well accommodated. In this study, we develop the structured G-E interaction analysis, where such structures are accommodated using penalization for both the main G effects and interactions. Penalization is also applied for regularized estimation and selection. The proposed structured interaction analysis can be effectively realized. It is shown to have the consistency properties under high dimensional settings. Simulations and the analysis of GENEVA diabetes data with SNP measurements and TCGA melanoma data with gene expression measurements demonstrate its competitive practical performance.
报告人介绍：
刘卫东，上海交通大学自然科学研究院，教授。2008年在浙江大学获博士学位，2008-2011年在香港科技大学和美国宾夕法尼亚大学沃顿商学院从事博士后研究。 2018年获得国家杰出青年科学基金。研究领域为高维数据的统计推断，在统计学四大顶级期刊AOS,JASA,JRSSB,Biometrika 和概率论顶级期刊 AOP,PTRF等发表四十余篇论文。
