Convergence of Descent Optimization Algorithms under Polyak-Łojasiewicz-Kurdyka Conditions

Fuente: arXiv
Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Bento, G. C., Mordukhovich, B. S., Mota, T. S., Nesterov, Yu.
Format: Preprint
Veröffentlicht: 2024
Schlagworte:
Online-Zugang:
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1866909488802430976
author Bento, G. C.
Mordukhovich, B. S.
Mota, T. S.
Nesterov, Yu.
author_facet Bento, G. C.
Mordukhovich, B. S.
Mota, T. S.
Nesterov, Yu.
contents This paper develops a comprehensive convergence analysis for generic classes of descent algorithms in nonsmooth and nonconvex optimization under several conditions of the Polyak-Łojasiewicz-Kurdyka (PLK) type. Along other results, we prove the finite termination of generic algorithms under the PLK conditions with lower exponents. Specifications are given to establish new convergence rates for inexact reduced gradient methods and some versions of the boosted algorithm in DC programming. It is revealed, e.g., that the lower exponent PLK conditions for a broad class of difference programs are incompatible with the gradient Lipschitz continuity for the plus function around a local minimizer. On the other hand, we show that the above inconsistency observation may fail if the Lipschitz continuity is replaced by merely the gradient continuity.
format Preprint
id arxiv_https___arxiv_org_abs_2407_00812
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Convergence of Descent Optimization Algorithms under Polyak-Łojasiewicz-Kurdyka Conditions
Bento, G. C.
Mordukhovich, B. S.
Mota, T. S.
Nesterov, Yu.
Optimization and Control
65K05, 65K10, 90C26, 47N10
This paper develops a comprehensive convergence analysis for generic classes of descent algorithms in nonsmooth and nonconvex optimization under several conditions of the Polyak-Łojasiewicz-Kurdyka (PLK) type. Along other results, we prove the finite termination of generic algorithms under the PLK conditions with lower exponents. Specifications are given to establish new convergence rates for inexact reduced gradient methods and some versions of the boosted algorithm in DC programming. It is revealed, e.g., that the lower exponent PLK conditions for a broad class of difference programs are incompatible with the gradient Lipschitz continuity for the plus function around a local minimizer. On the other hand, we show that the above inconsistency observation may fail if the Lipschitz continuity is replaced by merely the gradient continuity.
title Convergence of Descent Optimization Algorithms under Polyak-Łojasiewicz-Kurdyka Conditions
topic Optimization and Control
65K05, 65K10, 90C26, 47N10
url https://arxiv.org/abs/2407.00812