Online Program Home
My Program

Abstract Details

Activity Number: 466
Type: Invited
Date/Time: Wednesday, August 3, 2016 : 8:30 AM to 10:20 AM
Sponsor: IMS
Abstract #318041
Title: An Optimality of the L_0 Penalty and Dual Achievability of Model Selection
Author(s): Yuhong Yang*
Companies: University of Minnesota
Keywords: model selection consistency ; minimax estimation ; L_0 penalty ; dual achievability
Abstract:

We present a formal result on optimality of the L_0 penalty for variable selection in terms of the under-fitting and over-fitting probabilities. It is used to obtain a precise understanding on dual achievability of model selection, i.e., if and when we can achieve both model selection consistency and minimax rate estimation of the regression function in strong and weak senses. The work is joint with Zhan Wang.


Authors who are presenting talks have a * after their name.

Back to the full JSM 2016 program

 
 
Copyright © American Statistical Association