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dc.contributor.authorIbrahim, Shibal
dc.contributor.authorChen, Wenyu
dc.contributor.authorHazimeh, Hussein
dc.contributor.authorPonomareva, Natalia
dc.contributor.authorZhao, Zhe
dc.contributor.authorMazumder, Rahul
dc.date.accessioned2023-09-08T13:17:27Z
dc.date.available2023-09-08T13:17:27Z
dc.date.issued2023-08-06
dc.identifier.urihttps://hdl.handle.net/1721.1/152039
dc.publisherACM|Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Miningen_US
dc.relation.isversionofhttps://doi.org/10.1145/3580305.3599278en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceAssociation for Computing Machineryen_US
dc.titleCOMET: Learning Cardinality Constrained Mixture of Experts with Trees and Local Searchen_US
dc.typeArticleen_US
dc.identifier.citationIbrahim, Shibal, Chen, Wenyu, Hazimeh, Hussein, Ponomareva, Natalia, Zhao, Zhe et al. 2023. "COMET: Learning Cardinality Constrained Mixture of Experts with Trees and Local Search."
dc.contributor.departmentMassachusetts Institute of Technology. Operations Research Center
dc.contributor.departmentSloan School of Management
dc.contributor.departmentStatistics and Data Science Center (Massachusetts Institute of Technology)
dc.identifier.mitlicensePUBLISHER_CC
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.updated2023-09-01T07:46:10Z
dc.language.rfc3066en
dc.rights.holderThe author(s)
dspace.date.submission2023-09-01T07:46:10Z
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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