A modified Polak-Ribière-Polyak conjugate gradient algorithm for nonsmooth convex programs

YuanGonglin; WeiZengxin; LiGuoyin

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A modified Polak-Ribière-Polyak conjugate gradient algorithm for nonsmooth convex programs

YuanGonglin WeiZengxin LiGuoyin

Year: 2014 Journal: Journal of Computational and Applied Mathematics Publisher: Elsevier BV

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Abstract

The conjugate gradient (CG) method is one of the most popular methods for solving smooth unconstrained optimization problems due to its simplicity and low memory requirement. However, the usage of ...

Keywords:

Conjugate gradient method Mathematics Nonlinear conjugate gradient method Conjugate residual method Conjugate Derivation of the conjugate gradient method Simplicity Gradient method Convex optimization Regular polygon Convex function Algorithm Mathematical optimization Gradient descent Applied mathematics Mathematical analysis Computer science Geometry Artificial intelligence

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Advanced Optimization Algorithms Research

Physical Sciences → Mathematics → Numerical Analysis

Optimization and Variational Analysis

Physical Sciences → Computer Science → Computational Theory and Mathematics

Sparse and Compressive Sensing Techniques

Physical Sciences → Engineering → Computational Mechanics

A modified Polak-Ribière-Polyak conjugate gradient algorithm for nonsmooth convex programs

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