Solving constrained nonsmooth group sparse optimization via group Capped-ℓ1 relaxation and group smoothing proximal gradient algorithm

In this paper, we study the constrained group sparse regularization optimization problem, where the loss function is convex but nonsmooth, and the penalty term is the group sparsity which is then proposed to be relaxed by the group Capped- ℓ 1 for the convenience of computation. Firstly, we introduc...

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Bibliographic Details
Published in:	Computational optimization and applications Vol. 83; no. 3; pp. 801 - 844
Main Authors:	Zhang, Xian, Peng, Dingtao
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.12.2022 Springer Nature B.V
Subjects:	Algorithms Convex and Discrete Geometry Management Science Mathematics Mathematics and Statistics Operations Research Operations Research/Decision Theory Optimization Regularization Smoothing Statistics Constrained group sparse optimization Exact continuous relaxation 90C30 65K05 90C46 Lifted stationary points relaxation Group Capped Group smoothing proximal gradient algorithm 90C26
ISSN:	0926-6003, 1573-2894
Online Access:	Get full text
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