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Stein COnsistent Risk Estimator (SCORE) for hard thresholding

dc.contributor.authorFadili, Jalal
HAL ID: 15510
dc.contributor.authorPeyré, Gabriel
HAL ID: 1211
dc.contributor.authorDeledalle, Charles-Alban
dc.date.accessioned2013-01-16T14:17:26Z
dc.date.available2013-01-16T14:17:26Z
dc.date.issued2013
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/10848
dc.language.isoenen
dc.subjectrisk estimation
dc.subjectparameter selection
dc.subjectsparsity
dc.subjecthard thresholding
dc.subject.ddc621.3en
dc.titleStein COnsistent Risk Estimator (SCORE) for hard thresholding
dc.typeDocument de travail / Working paper
dc.contributor.editoruniversityotherGroupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen (GREYC) http://www.greyc.unicaen.fr/ CNRS : UMR6072 – Université de Caen Basse-Normandie – Ecole Nationale Supérieure d'Ingénieurs de Caen;France
dc.contributor.editoruniversityotherInstitut de Mathématiques de Bordeaux (IMB) http://www.math.u-bordeaux.fr/IMB/ CNRS : UMR5251 – Université Sciences et Technologies - Bordeaux I – Université Victor Segalen - Bordeaux II;France
dc.description.abstractenIn this work, we construct a risk estimator for hard thresholding which can be used as a basis to solve the difficult task of automatically selecting the threshold. As hard thresholding is not even continuous, Stein's lemma cannot be used to get an unbiased estimator of degrees of freedom, hence of the risk. We prove that under a mild condition, our estimator of the degrees of freedom, although biased, is consistent. Numerical evidence shows that our estimator outperforms another biased risk estimator.
dc.publisher.cityParisen
dc.relation.ispartofseriestitleUniversité Paris-Dauphine
dc.subject.ddclabelTraitement du signalen
dc.description.submittednonen
dc.description.ssrncandidatenon
dc.description.halcandidateoui
dc.description.readershiprecherche
dc.description.audienceInternational
dc.date.updated2017-09-21T13:46:17Z


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