AbstractGenetical genomics data present promising opportunities for integrating gene expression and genotype information. Lin et al. (2015) proposed an instrumental variables (IV) regression framework to select important genes with high-dimensional genetical genomics data. The IV regression addresses the issue of endogeneity caused by potential correlations between gene expressions and error te...
Description:High-dimensional statistical learning has become an increasingly important research area. In this course, we will provide theoretical foundations of high-dimensional learning for several widely studied problems with many applications. More specifically, we will review concentration inequalities, VC dimension, metric entropy and statistical implications, consider high-dimensional lin...