Re-thinking High-dimensional Mathematical Statistics

dc.bibliographicCitation.firstPage1377
dc.bibliographicCitation.issue2
dc.bibliographicCitation.journalTitleOberwolfach reports : OWR
dc.bibliographicCitation.lastPage1430
dc.bibliographicCitation.volume19
dc.contributor.otherBunea, Florentina
dc.contributor.otherNowak, Robert
dc.contributor.otherTsybakov, Alexandre
dc.date.accessioned2024-10-17T12:12:48Z
dc.date.available2024-10-17T12:12:48Z
dc.date.issued2022
dc.description.abstractThe workshop highlighted recent theoretical advances on inference in high-dimensional statistical models based on the interplay of techniques from mathematical statistics, machine learning, theoretical computer science and related areas. The workshop brought together about 50 researchers in order to present new results, exchange ideas and explore open problems.eng
dc.description.versionpublishedVersion
dc.identifier.urihttps://oa.tib.eu/renate/handle/123456789/17023
dc.identifier.urihttps://doi.org/10.34657/16045
dc.language.isoeng
dc.publisherZürich : EMS Publ. House
dc.relation.doihttps://doi.org/10.4171/OWR/2022/25
dc.relation.essn1660-8941
dc.relation.issn1660-8933
dc.rights.licenseThis 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.licenseDieses 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.ddc510
dc.subject.gndKonferenzschriftger
dc.titleRe-thinking High-dimensional Mathematical Statisticseng
dc.typeArticle
tib.accessRightsopenAccess
wgl.contributorMFO
wgl.subjectMathematik
wgl.typeZeitschriftenartikel

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