A Generalized Accelerated Gradient Optimization Method

Alex Xinting Wu, Ian R. Petersen, Valery Ugrinovskii, Iman Shames

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

In this paper, we extend the recently developed generalized heavy ball optimization algorithm by introducing an additional parameter. This yields an improved optimization algorithm which has a similar form to the triple momentum method. The global convergence of the proposed algorithm for a class of functions with sector-bounded gradients is established. This is achieved by using the circle criterion. The proposed algorithm is designed to have the best possible R-convergence rate consistent with global convergence established using the circle criterion.

Original languageEnglish
Title of host publication2024 American Control Conference, ACC 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1904-1908
Number of pages5
ISBN (Electronic)9798350382655
DOIs
Publication statusPublished - 2024
Event2024 American Control Conference, ACC 2024 - Toronto, Canada
Duration: 10 Jul 202412 Jul 2024

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619

Conference

Conference2024 American Control Conference, ACC 2024
Country/TerritoryCanada
CityToronto
Period10/07/2412/07/24

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