Skip to content

A probabilistic solution to the exact best subset selection problem via continuous reformulation and gradient-based optimization.

Notifications You must be signed in to change notification settings

mingzhang-yin/Probabilistic-Best-Subset

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

16 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Probabilistic-Best-Subset-Selection

Best subset selection methods as described in Probabilistic Best Subset Selection via Gradient-Based Optimization

Directories

  • The Jupyter Notebook demonstrations are in the folder ./demo
  • The folders ./experiment-i are the example folders that contain the executable scripts for the simulations in the paper
  • The R scripts produce LASSO, SCAD and Fast-BSS results and the U2G results are produced by bash run.sh
@article{yin2020probabilistic,
     author = {{Yin}, Mingzhang and {Ho}, Nhat and {Yan}, Bowei and {Qian}, Xiaoning and
               {Zhou}, Mingyuan},
     title = "{Probabilistic Best Subset Selection via Gradient-Based Optimization}",
     journal = {arXiv},
     year = 2020
}

About

A probabilistic solution to the exact best subset selection problem via continuous reformulation and gradient-based optimization.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published