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...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Computational optimization and applications Ročník 83; číslo 3; s. 801 - 844
Hlavní autoři:	Zhang, Xian, Peng, Dingtao
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Springer US 01.12.2022 Springer Nature B.V
Témata:	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
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!