# The Benefit of Group Sparsity

@article{Huang2009TheBO,
title={The Benefit of Group Sparsity},
author={Junzhou Huang and Tong Zhang},
journal={Annals of Statistics},
year={2009},
volume={38},
pages={1978-2004}
}
• Published 20 January 2009
• Computer Science, Mathematics
• Annals of Statistics
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.
482 Citations

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