University of Illinois at Chicago
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Assorted Techniques for Handling High Dimensional Data

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posted on 2022-05-01, 00:00 authored by Yushen Dong
Techniques of handling high-dimensional data is a really active research area lately as data collection and storage methods are advanced now. Variable selection and dimension reduction are two main sections of this area. In this dissertation, we introduce three techniques for dealing with situations where the number of predictors is extremely high, which are suited for various data types and models.

History

Advisor

Wu, Yichao

Chair

Wu, Yichao

Department

Mathematics, Statistics, & Computer Science

Degree Grantor

University of Illinois at Chicago

Degree Level

  • Doctoral

Degree name

PhD, Doctor of Philosophy

Committee Member

Min, Yang Wang, Jing Yang, Jie Chen, Hua Yun

Submitted date

May 2022

Thesis type

application/pdf

Language

  • en

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