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Avtomatika i Telemekhanika, 2014, Issue 4, Pages 67–80 (Mi at7532)  
This article is cited in 11 scientific papers (total in 11 papers)

Mathematical programming problems

Method of conjugate subgradients with constrained memory

E. A. Nurminskiiab, D. Tienc

a Institute of Automation and Control Processes, Far-Eastern Branch, Russian Academy of Sciences, Vladivostok, Russia
b Far-Eastern Federal University, Vladivostok, Russia
c Charles Stuart University, Bathurst, Australia
Full-text PDF (518 kB) Citations (11)
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Abstract: A method to solve the convex problems of nondifferentiable optimization relying on the basic philosophy of the method of conjugate gradients and coinciding with it in the case of quadratic functions was presented. Its basic distinction from the earlier counterparts lies in the a priori fixed constraint on the memory size which is independent of the accuracy of the resulting solution. Numerical experiments suggest practically linear rate of convergence of this algorithm.
Presented by the member of Editorial Board: A. I. Kibzun

Received: 14.11.2013
English version:
Automation and Remote Control, 2014, Volume 75, Issue 4, Pages 646–656
DOI: https://doi.org/10.1134/S0005117914040055
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: E. A. Nurminskii, D. Tien, “Method of conjugate subgradients with constrained memory”, Avtomat. i Telemekh., 2014, no. 4, 67–80; Autom. Remote Control, 75:4 (2014), 646–656
Citation in format AMSBIB
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\paper Method of conjugate subgradients with constrained memory
\jour Avtomat. i Telemekh.
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\pages 646--656
\crossref{https://doi.org/10.1134/S0005117914040055}
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  • https://www.mathnet.ru/eng/at/y2014/i4/p67
    • This publication is cited in the following 11 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
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    Abstract page:257
    Full-text PDF :75
    References:58
    First page:21
     
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