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A Data Science Perspective on Deconvolution

dc.contributor.authorBunse, Mirko
dc.contributor.authorPiatkowski, Nico
dc.contributor.authorRuhe, Tim
dc.contributor.authorMorik, Katharina
dc.contributor.authorRhode, Wolfgang
dc.contributor.editorDavid, Klaus
dc.contributor.editorGeihs, Kurt
dc.contributor.editorLange, Martin
dc.contributor.editorStumme, Gerd
dc.date.accessioned2019-08-27T12:55:25Z
dc.date.available2019-08-27T12:55:25Z
dc.date.issued2019
dc.identifier.doi10.18420/inf2019_43
dc.identifier.isbn978-3-88579-688-6
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/24992
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofINFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-294
dc.subjectdeconvolution
dc.subjectunfolding
dc.subjectsupervised learning
dc.subjecttransductive learning
dc.subjectdensity estimation
dc.subjectCherenkov astronomy
dc.subjectregularization
dc.titleA Data Science Perspective on Deconvolutionen
dc.typeText/Conference Paper
gi.citation.endPage280
gi.citation.publisherPlaceBonn
gi.citation.startPage279
gi.conference.date23.-26. September 2019
gi.conference.locationKassel
gi.conference.sessiontitleData Science

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