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dc.contributor.authorBelkin, M
dc.contributor.authorRakhlin, A
dc.contributor.authorTsybakov, AB
dc.date.accessioned2021-12-03T15:23:42Z
dc.date.available2021-12-03T15:23:42Z
dc.date.issued2020-01-01
dc.identifier.urihttps://hdl.handle.net/1721.1/138307
dc.description.abstract© 2019 by the author(s). We show that classical learning methods interpolating the training data can achieve optimal rates for the problems of nonparametric regression and prediction with square loss.en_US
dc.language.isoen
dc.relation.isversionofhttps://proceedings.mlr.press/v89/belkin19a.htmlen_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceProceedings of Machine Learning Researchen_US
dc.titleDoes data interpolation contradict statistical optimality?en_US
dc.typeArticleen_US
dc.identifier.citationBelkin, M, Rakhlin, A and Tsybakov, AB. 2020. "Does data interpolation contradict statistical optimality?." AISTATS 2019 - 22nd International Conference on Artificial Intelligence and Statistics, 89.
dc.relation.journalAISTATS 2019 - 22nd International Conference on Artificial Intelligence and Statisticsen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2021-12-03T15:12:02Z
dspace.orderedauthorsBelkin, M; Rakhlin, A; Tsybakov, ABen_US
dspace.date.submission2021-12-03T15:12:03Z
mit.journal.volume89en_US
mit.licensePUBLISHER_POLICY
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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