Mini-Workshop: Mathematical Foundations of Robust and Generalizable Learning

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dc.bibliographicCitation.journalTitleOberwolfach reports : OWR
dc.bibliographicCitation.volume46
dc.contributor.otherLederer, Johannes
dc.contributor.otherLoh, Po-Ling
dc.contributor.otherWei, Yuting
dc.contributor.otherYang, Fanny
dc.date.accessioned2024-10-17T12:16:25Z
dc.date.available2024-10-17T12:16:25Z
dc.date.issued2022
dc.description.abstractMachine learning has become an highly active field of research, but its mathematical underpinnings are still hardly understood. This workshop identified key challenges, and it discussed potential solutions. Bringing together a diverse group of researchers, the workshop established different views on the topic based on notions from statistics, probability theory, and optimization.
dc.description.versionpublishedVersion
dc.identifier.urihttps://oa.tib.eu/renate/handle/123456789/17051
dc.identifier.urihttps://doi.org/10.34657/16073
dc.language.isoeng
dc.publisherOberwolfach : Mathematisches Forschungsinstitut Oberwolfach
dc.relation.doihttps://doi.org/10.14760/OWR-2022-46
dc.relation.essn1660-8941
dc.relation.issn1660-8933
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.
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.
dc.subject.ddc510
dc.subject.gndKonferenzschrift
dc.titleMini-Workshop: Mathematical Foundations of Robust and Generalizable Learning
dc.typeArticle
dc.typeText
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