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seminars:stat:190425

Statistics Seminar
Department of Mathematical Sciences

DATE:Thursday, April 25, 2019
TIME:1:15pm – 2:15pm
LOCATION:WH 100E
SPEAKER:Cun-hui Zhang, Rutgers University
TITLE:Semi-Low-Dimensional Inference With High-Dimensional Data


Abstract

We consider statistical inference in a semi-low-dimensional approach to the analysis of high-dimensional data. The relationship between this semi-low-dimensional approach and regularized estimation of high-dimensional objects is parallel to the more familiar one between semiparametric analysis and nonparametric estimation. Low-dimensional projection methods are used to correct the bias of regularized high-dimensional estimators, leading to efficient point and interval estimation. Bootstrap can be used to carry out simultaneous inference. Only a small fraction of labelled data are needed in a semisupervised setting. Examples include regression and graphical models for continuous and binary data.

seminars/stat/190425.txt · Last modified: 2018/09/25 07:58 by qiao