Delayed Weighted Gradient Method with simultaneous step-sizes for strongly convex optimization

The Delayed Weighted Gradient Method (DWGM) is a two-step gradient algorithm that is efficient for the minimization of large scale strictly convex quadratic functions. It has orthogonality properties that make it to compete with the Conjugate Gradient (CG) method. Both methods calculate in sequence...

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Veröffentlicht in:	Computational optimization and applications Jg. 89; H. 1; S. 151 - 182
Hauptverfasser:	Lara, Hugo, Aleixo, Rafael, Oviedo, Harry
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.09.2024 Springer Nature B.V
Schlagworte:	Algorithms Conjugate gradient method Convex analysis Convex and Discrete Geometry Convexity Management Science Mathematics Mathematics and Statistics Methods Operations Research Operations Research/Decision Theory Optimization Orthogonality Quadratic equations Statistics Two dimensional analysis Gradient methods Strongly convex functions Conjugate gradient methods Large-scale optimization
ISSN:	0926-6003, 1573-2894
Online-Zugang:	Volltext
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