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

Author

Yuan, Gonglin, Sheng, Zhou, and Liu, Wenjie

Subjects
NONSMOOTH optimization, CONJUGATE gradient methods, STOCHASTIC convergence, NUMERICAL analysis, CONVEX functions
Abstract

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). [ABSTRACT FROM AUTHOR]

Published
2016
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