Convergence Rate of Descent Method with New Inexact Line-Search on Riemannian Manifolds

Xiao bo Li, Nan jing Huang, Qamrul Hasan Ansari*, Jen Chih Yao

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

In this paper, we propose the descent method with new inexact line-search for unconstrained optimization problems on Riemannian manifolds. The global convergence of the proposed method is established under some appropriate assumptions. We further analyze some convergence rates, namely R-linear convergence rate, superlinear convergence rate and quadratic convergence rate, of the proposed descent method.

Original languageEnglish
Pages (from-to)830-854
Number of pages25
JournalJournal of Optimization Theory and Applications
Volume180
Issue number3
DOIs
StatePublished - 15 Mar 2019

Bibliographical note

Publisher Copyright:
© 2018, Springer Science+Business Media, LLC, part of Springer Nature.

Keywords

  • Convergence rate
  • Descent method
  • New inexact line-search
  • Riemannian manifolds

ASJC Scopus subject areas

  • Management Science and Operations Research
  • Control and Optimization
  • Applied Mathematics

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