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Avtomatika i Telemekhanika, 2017, Issue 2, Pages 36–49 (Mi at14682)  
This article is cited in 35 scientific papers (total in 35 papers)

Stochastic Systems, Queuing Systems

Stochastic online optimization. Single-point and multi-point non-linear multi-armed bandits. Convex and strongly-convex case

A. V. Gasnikovab, E. A. Krymovab, A. A. Lagunovskayaca, I. N. Usmanovaab, F. A. Fedorenkoa

a Moscow Institute of Physics and Technology (State University), Moscow, Russia
b Institute for Information Transmission Problems (Kharkevich Institute), Russian Academy of Sciences, Moscow, Russia
c Keldysh Institute of Applied Mathematics, Russian Academy of Sciences, Moscow, Russia
Full-text PDF (673 kB) Citations (35)
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Abstract: In this paper the gradient-free modification of the mirror descent method for convex stochastic online optimization problems is proposed. The crucial assumption in the problem setting is that function realizations are observed with minor noises. The aim of this paper is to derive the convergence rate of the proposed methods and to determine a noise level which does not significantly affect the convergence rate.
Keywords: online optimization, gradient-free, inexact oracle, stochastic optimization.
Funding agency Grant number
Russian Foundation for Basic Research 15-31-20571 мол_а_вед
Russian Science Foundation 14-50-00150
This work was supported by the Russian Foundation for Basic Research, project no. 15-31-20571 mol_a_ved. The work of the first two authors was partially supported by the Russian Science Foundation, project no. 14-50-00150 in Institute for Information Transmission Problems of the Russian Academy of Sciences.
Presented by the member of Editorial Board: P. S. Shcherbakov

Received: 16.10.2014
English version:
Automation and Remote Control, 2017, Volume 78, Issue 2, Pages 224–234
DOI: https://doi.org/10.1134/S0005117917020035
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: A. V. Gasnikov, E. A. Krymova, A. A. Lagunovskaya, I. N. Usmanova, F. A. Fedorenko, “Stochastic online optimization. Single-point and multi-point non-linear multi-armed bandits. Convex and strongly-convex case”, Avtomat. i Telemekh., 2017, no. 2, 36–49; Autom. Remote Control, 78:2 (2017), 224–234
Citation in format AMSBIB
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\paper Stochastic online optimization. Single-point and multi-point non-linear multi-armed bandits. Convex and strongly-convex case
\jour Avtomat. i Telemekh.
\yr 2017
\issue 2
\pages 36--49
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\jour Autom. Remote Control
\yr 2017
\vol 78
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\pages 224--234
\crossref{https://doi.org/10.1134/S0005117917020035}
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    • This publication is cited in the following 35 articles:
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