Globally linearly convergent nonlinear conjugate gradients without Wolfe line search

Arnold Neumaier, Morteza Kimiaei, Behzad Azmi

Veröffentlichungen: Beitrag in FachzeitschriftArtikelPeer Reviewed

Abstract

This paper introduces a new nonlinear conjugate gradient method using any efficient line search method. Unless function values diverge to $-\infty$, global convergence to a stationary point is proved for continuously differentiable objective functions with Lipschitz continuous gradient, and global linear convergence if this stationary point is a strong local minimizer. Complexity bounds are given for the number of function evaluations for approximating a stationary point.
OriginalspracheEnglisch
FachzeitschriftNumerical Algorithms
PublikationsstatusVeröffentlicht - 9 Feb. 2024

ÖFOS 2012

  • 101016 Optimierung
  • 101014 Numerische Mathematik

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