SWAGGER: sparsity within and across groups for general estimation and recovery
Files
First author draft
Date
2020
DOI
Authors
Saunders, Charles
Goyal, Vivek K.
Version
First author draft
OA Version
Citation
Charles Saunders, Vivek K Goyal. "SWAGGER: Sparsity Within and Across Groups for General Estimation and Recovery." https://arxiv.org/abs/2006.01714
Abstract
Penalty functions or regularization terms that promote structured solutions to optimization problems are of great interest in many fields. Proposed in this work is a nonconvex structured sparsity penalty that promotes one-sparsity within arbitrary overlapping groups in a vector. This allows one to enforce mutual exclusivity between components within solutions to optimization problems. We show multiple example use cases (including a total variation variant), demonstrate synergy between it and other regularizers, and propose an algorithm to efficiently solve problems regularized or constrained by the proposed penalty.