The Benefit of Group Sparsity

Preprint

17 March 2009

preprint
Published by arXiv in arXiv

https://doi.org/10.48550/arXiv.0901.2962

Abstract

This paper develops a theory for group Lasso using a concept called strong group sparsity. Our result shows that group Lasso is superior to standard Lasso for strongly group-sparse signals. This provides a convincing theoretical justification for using group sparse regularization when the underlying group structure is consistent with the data. Moreover, the theory predicts some limitations of the group Lasso formulation that are confirmed by simulation studies.

Keywords

GROUP SPARSITY
CONCEPT CALLED
CALLED STRONG
GROUP SPARSE
LASSO USING
GROUP LASSO
SIMULATION
SPARSITY

All Related Versions

Version 1, 2009-01-20, ArXiv
Version 2, 2009-03-17, ArXiv

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