Abstract: This paper aims to identify the current state of the art of the latest research related to Conjugate Gradient (CG) methods for unconstrained optimization through a systematic literature ...

The nonlinear conjugate gradient method is a very useful technique for solving large scale minimization problems and has wide applications in many fields. In this paper, we present a new algorithm of ...

ABSTRACT: In conjugate gradient method, it is well known that the recursively computed residual differs from true one as the iteration proceeds in finite arithmetic. Some work have been devoted to ...

Abstract: In the paper “Applications of the conjugate gradient fast Fourier Hankel transfer method with an improved fast Hankel transform algorithm” by Qing-Huo Liu and Weng Cho Chew (Radio Science, ...

Conjugate gradient method is a numerical method that can find the minima of the function in the hyper-dimensional space, and conjugate gradient method includes linear conjugate method and non-linear ...

ABSTRACT: In this paper, a new nonlinear conjugate gradient method is proposed for large-scale unconstrained optimization. The sufficient descent property holds without any line searches. We use some ...

NCG-Optimizer is a set of optimizer about nonlinear conjugate gradient in PyTorch. Inspired by @jettify and @kozistr. The Linear Conjugate Gradient(LCG) method is only applicable to linear equation ...