JSM 2012 Home

JSM 2012 Online Program

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

Online Program Home

Abstract Details

Activity Number: 466
Type: Contributed
Date/Time: Wednesday, August 1, 2012 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistical Learning and Data Mining
Abstract - #304231
Title: Variable Selection via Subtle Uprooting
Author(s): Xiaogang Su*+
Companies: The University of Alabama at Birmingham
Address: Center for Nursing Research, Birmingham, AL, 35294-1210, United States
Keywords: Variable Selection ; Non-Convex Penalty ; L1 Regularization ; AIC ; BIC
Abstract:

A simple variable selection method termed "subtle uprooting" is put forward for linear regression. In this method, variable selection is formulated as a non-convex programming problem in a penalized function form. The significance of this method is that tuning the penalty parameter and hence computing the whole regularization path are avoided. The solution of the problem can be conveniently obtained via coordinate descent (also aided with some global optimization routines). Both theoretical insight and empirical evidence are provided to support and illustrate how promising the proposed method is.


The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.

Back to the full JSM 2012 program




2012 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Continuing Education program, please contact the Education Department.