Gradient methods for problems with inexact model of the objective
dc.bibliographicCitation.seriesTitle | WIAS Preprints | eng |
dc.bibliographicCitation.volume | 2688 | |
dc.contributor.author | Stonyakin, Fedor | |
dc.contributor.author | Dvinskikh, Darina | |
dc.contributor.author | Dvurechensky, Pavel | |
dc.contributor.author | Kroshnin, Alexey | |
dc.contributor.author | Kuznetsova, Olesya | |
dc.contributor.author | Agafonov, Artem | |
dc.contributor.author | Gasnikov, Alexander | |
dc.contributor.author | Tyurin, Alexander | |
dc.contributor.author | Uribe, Cesar A. | |
dc.contributor.author | Pasechnyuk, Dmitry | |
dc.contributor.author | Artamonov, Sergei | |
dc.date.accessioned | 2022-06-30T12:42:34Z | |
dc.date.available | 2022-06-30T12:42:34Z | |
dc.date.issued | 2020 | |
dc.description.abstract | We consider optimization methods for convex minimization problems under inexact information on the objective function. We introduce inexact model of the objective, which as a particular cases includes inexact oracle [19] and relative smoothness condition [43]. We analyze gradient method which uses this inexact model and obtain convergence rates for convex and strongly convex problems. To show potential applications of our general framework we consider three particular problems. The first one is clustering by electorial model introduced in [49]. The second one is approximating optimal transport distance, for which we propose a Proximal Sinkhorn algorithm. The third one is devoted to approximating optimal transport barycenter and we propose a Proximal Iterative Bregman Projections algorithm. We also illustrate the practical performance of our algorithms by numerical experiments. | eng |
dc.description.version | publishedVersion | eng |
dc.identifier.uri | https://oa.tib.eu/renate/handle/123456789/9338 | |
dc.identifier.uri | https://doi.org/10.34657/8376 | |
dc.language.iso | eng | |
dc.publisher | Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik | |
dc.relation.doi | https://doi.org/10.20347/WIAS.PREPRINT.2688 | |
dc.relation.issn | 2198-5855 | |
dc.rights.license | This document may be downloaded, read, stored and printed for your own use within the limits of § 53 UrhG but it may not be distributed via the internet or passed on to external parties. | eng |
dc.rights.license | Dieses Dokument darf im Rahmen von § 53 UrhG zum eigenen Gebrauch kostenfrei heruntergeladen, gelesen, gespeichert und ausgedruckt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden. | ger |
dc.subject.ddc | 510 | |
dc.subject.other | Gradient method | eng |
dc.subject.other | inexact oracle | eng |
dc.subject.other | strong convexity | eng |
dc.subject.other | relative smoothness | eng |
dc.subject.other | Bregman divergence | eng |
dc.title | Gradient methods for problems with inexact model of the objective | eng |
dc.type | Report | eng |
dc.type | Text | eng |
dcterms.extent | 30 S. | |
tib.accessRights | openAccess | |
wgl.contributor | WIAS | |
wgl.subject | Mathematik | |
wgl.type | Report / Forschungsbericht / Arbeitspapier |
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