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hal.structure.identifierGroupe de Recherche en Informatique, Image et Instrumentation de Caen [GREYC]
dc.contributor.authorLiang, Jingwei
HAL ID: 10273
hal.structure.identifierGroupe de Recherche en Informatique, Image et Instrumentation de Caen [GREYC]
dc.contributor.authorFadili, Jalal M.
HAL ID: 15510
hal.structure.identifierCEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
dc.contributor.authorPeyré, Gabriel
HAL ID: 1211
dc.date.accessioned2020-06-09T14:03:10Z
dc.date.available2020-06-09T14:03:10Z
dc.date.issued2015
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/20862
dc.language.isoenen
dc.subjectForward-Backward Splittingen
dc.subject.ddc621.3en
dc.titleLocal Linear Convergence of Inertial Forward-Backward Splitting for Low Complexity Regularizationen
dc.typeCommunication / Conférence
dc.description.abstractenIn this abstract, we consider the inertial Forward-Backward (iFB) splitting method and its special cases (Forward-Backward/ISTA and FISTA). Under the assumption that the non-smooth part of the objective is partly smooth relative to an active smooth manifold, we show that iFB-type methods (i) identify the active manifold in finite time, then (ii) enter a local linear convergence regime that we characterize precisely. This gives a grounded and unified explanation to the typical behaviour that has been observed numerically for many low-complexity regularizers, including 1 , 1,2-norms, total variation (TV) and nuclear norm to name a few. The obtained results are illustrated by concrete examples.en
dc.subject.ddclabelTraitement du signalen
dc.relation.conftitleSPARSen
dc.relation.confdate2015
dc.relation.confcityCambridgeen
dc.relation.confcountryUnited Kingdomen
dc.relation.forthcomingnonen
dc.description.ssrncandidatenonen
dc.description.halcandidatenonen
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.relation.Isversionofjnlpeerreviewednonen
dc.relation.Isversionofjnlpeerreviewednonen
dc.date.updated2020-06-09T13:58:07Z
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