CONVERGENCE OF ZH-TYPE NONMONOTONE DESCENT METHOD FOR KURDYKA-ŁOJASIEWICZ OPTIMIZATION PROBLEMS

  • Yitian Qian
  • , Ting Tao
  • , Shaohua Pan
  • , Houduo Qi

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)

Abstract

We propose a novel iterative framework for minimizing a proper lower semicontinuous Kurdyka-\ Lojasiewicz (KL) function \Phi. It comprises a Zhang-Hager (ZH-type) nonmonotone decrease condition and a relative error condition. Hence, the sequence generated by the ZH-type nonmonotone descent methods will fall within this framework. Any sequence conforming to this framework is proved to converge to a critical point of \Phi. If in addition \Phi has the KL property of exponent \theta\in (0, 1) at the critical point, the convergence has a linear rate for \theta \in (0, 1/2] and a sub-linear rate of exponent 112\theta\theta for \theta \in (1/2, 1). To the best of our knowledge, this is the first work to establish the full convergence of the iterate sequence generated by a ZH-type nonmonotone descent method for nonconvex and nonsmooth optimization problems. The obtained results are also applied to achieve the full convergence of the iterate sequences produced by the proximal gradient method and Riemannian gradient method with the ZH-type nonmonotone line-search.

Original languageEnglish
Pages (from-to)1089-1109
Number of pages21
JournalSIAM Journal on Optimization
Volume35
Issue number2
DOIs
Publication statusPublished - May 2025

Keywords

  • full convergence
  • KL property
  • nonconvex and nonsmooth optimization
  • proximal gradient methods
  • ZH-type nonmonotone descent method

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Applied Mathematics

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