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Does data interpolation contradict statistical optimality?
dc.contributor.author | Belkin, M | |
dc.contributor.author | Rakhlin, A | |
dc.contributor.author | Tsybakov, AB | |
dc.date.accessioned | 2021-12-03T15:23:42Z | |
dc.date.available | 2021-12-03T15:23:42Z | |
dc.date.issued | 2020-01-01 | |
dc.identifier.uri | https://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.iso | en | |
dc.relation.isversionof | https://proceedings.mlr.press/v89/belkin19a.html | en_US |
dc.rights | Article 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.source | Proceedings of Machine Learning Research | en_US |
dc.title | Does data interpolation contradict statistical optimality? | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Belkin, 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.journal | AISTATS 2019 - 22nd International Conference on Artificial Intelligence and Statistics | en_US |
dc.eprint.version | Final published version | en_US |
dc.type.uri | http://purl.org/eprint/type/ConferencePaper | en_US |
eprint.status | http://purl.org/eprint/status/NonPeerReviewed | en_US |
dc.date.updated | 2021-12-03T15:12:02Z | |
dspace.orderedauthors | Belkin, M; Rakhlin, A; Tsybakov, AB | en_US |
dspace.date.submission | 2021-12-03T15:12:03Z | |
mit.journal.volume | 89 | en_US |
mit.license | PUBLISHER_POLICY | |
mit.metadata.status | Authority Work and Publication Information Needed | en_US |