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Application of the Infinitely Many Times Repeated BNS Update and Conjugate Directions to Limited-Memory Optimization Methods

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    SYSNO ASEP0504548
    Document TypeC - Proceedings Paper (int. conf.)
    R&D Document TypeConference Paper
    TitleApplication of the Infinitely Many Times Repeated BNS Update and Conjugate Directions to Limited-Memory Optimization Methods
    Author(s) Vlček, Jan (UIVT-O) SAI, RID, ORCID
    Lukšan, Ladislav (UIVT-O) SAI, RID
    Source TitlePrograms and Algorithms of Numerical Mathematics 19. - Prague : Institute of Mathematics of the Czech Academy of Sciences, 2019 / Chleboun J. ; Kůs P. ; Přikryl P. ; Rozložník M. ; Segeth K. ; Šístek J. ; Vejchodský T. - ISBN 978-80-85823-69-1
    Pagess. 177-185
    Number of pages9 s.
    Publication formOnline - E
    ActionPrograms and Algorithms of Numerical Mathematics /19./
    Event date24.06.2018 - 29.06.2018
    VEvent locationHejnice
    CountryCZ - Czech Republic
    Event typeWRD
    Languageeng - English
    CountryCZ - Czech Republic
    Keywordsunconstrained minimization ; limited-memory variable metric methods ; the repeated Byrd-Nocedal-Schnabel update ; the Lyapunov matrix equation ; the conjugate directions ; global convergence ; numerical results
    Subject RIVBA - General Mathematics
    OECD categoryApplied mathematics
    Institutional supportUIVT-O - RVO:67985807
    UT WOS000576737400019
    DOI10.21136/panm.2018.19
    AnnotationTo improve the performance of the L-BFGS method for large scale unconstrained optimization, repeating of some BFGS updates was proposed. Since this can be time consuming, the extra updates need to be selected carefully. We show that groups of these updates can be repeated infinitely many times under some conditions, without a noticeable increase of the computational time. The limit update is a block BFGS update. It can be obtained by solving of some Lyapunov matrix equation whose order can be decreased by application of vector corrections for conjugacy. Global convergence of the proposed algorithm is established for convex and sufficiently smooth functions. Numerical results indicate the efficiency of the new method.
    WorkplaceInstitute of Computer Science
    ContactTereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
    Year of Publishing2020
Number of the records: 1  

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