The Modified HZ Conjugate Gradient Algorithm for Large-Scale Nonsmooth Optimization

In this paper, the Hager and Zhang (HZ) conjugate gradient (CG) method and the modified HZ (MHZ) CG method are presented for large-scale nonsmooth convex minimization. Under some mild conditions, convergent results of the proposed methods are established. Numerical results show that the presented me...

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Detalles Bibliográficos
Autores principales: Yuan, Gonglin, Sheng, Zhou, Liu, Wenjie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5079589/
https://www.ncbi.nlm.nih.gov/pubmed/27780245
http://dx.doi.org/10.1371/journal.pone.0164289
Descripción
Sumario:In this paper, the Hager and Zhang (HZ) conjugate gradient (CG) method and the modified HZ (MHZ) CG method are presented for large-scale nonsmooth convex minimization. Under some mild conditions, convergent results of the proposed methods are established. Numerical results show that the presented methods can be better efficiency for large-scale nonsmooth problems, and several problems are tested (with the maximum dimensions to 100,000 variables).

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