On convergence of iterative thresholding algorithms to approximate sparse solution for composite nonconvex optimization

This paper aims to find an approximate true sparse solution of an underdetermined linear system. For this purpose, we propose two types of iterative thresholding algorithms with the continuation technique and the truncation technique respectively. We introduce a notion of limited shrinkage threshold...

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Vydané v:	Mathematical programming Ročník 211; číslo 1-2; s. 181 - 206
Hlavní autori:	Hu, Yaohua, Hu, Xinlin, Yang, Xiaoqi
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Heidelberg Springer Nature B.V 01.05.2025
Predmet:	Algorithms Approximation Convergence Fines & penalties Linear systems Noise levels Noise tolerance Optimization algorithms Regularization Regularization methods Sparsity
ISSN:	0025-5610, 1436-4646
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