Bilevel Learning of the Group Lasso Structure
- author: Jordan Frecon
- institution: Computational Statistics and Machine Learning, Istituto Italiano di Tecnologia, Genova, Italy *
- date: January 14 2019
- License CeCILL-B
RECOMMENDATIONS: This toolbox is designed to work with Matlab 2017.a
DESCRIPTION: This toolbox provides an efficient way to learn the groups in Group Lasso. The proposed framework is based on a continuous bilevel formulation of the problem of learning the groups. Our approach relies on an approximation where the lower problem is replaced by a smooth dual forward-backward scheme with Bregman distances
This toolbox consists of 2 subfolders containing MATLAB functions designed for the proposed algorithm.
SPECIFICATIONS for using BiGLasso:
One demo file 'demo_BiGLasso.m' is proposed to illustrate the principle of the method with dynamic displays The main function is 'BiGLasso.m'
RELATED PUBLICATION:
J. Frecon, S. Salzo, and M. Pontil, "Bilevel Learning of Group Lasso Structure", Thirty-Second Annual Conference on Neural Information Processing Systems (NIPS 2018).