A three-block linearized generalized ADMM based iterative algorithm for separable convex programming with application to an image compression problem

The generalized alternating direction method of multipliers (GADMM) has attracted considerable attention due to its versatile applications. This study introduces an innovative adaptation called the linearized GADMM (L-GADMM), which is specifically tailored for solving convex optimization problems. T...

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Veröffentlicht in:	Journal of computational and applied mathematics Jg. 462; S. 116483
Hauptverfasser:	Zhang, Xueqing, Peng, Jianwen, Ghosh, Debdas, Yao, Jen-Chih
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.07.2025
Schlagworte:	Generalized ADMM Global convergence Image compression Linearized ADMM Separable convex optimization Linearized ADMM Global convergence Image compression Generalized ADMM Separable convex optimization
ISSN:	0377-0427
Online-Zugang:	Volltext
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