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dc.contributor.authorIbrahim, Shibal
dc.contributor.authorHazimeh, Hussein
dc.contributor.authorMazumder, Rahul
dc.date.accessioned2022-11-10T18:42:42Z
dc.date.available2022-11-10T18:42:42Z
dc.date.issued2022-08-14
dc.identifier.isbn978-1-4503-9385-0
dc.identifier.urihttps://hdl.handle.net/1721.1/146341
dc.publisherACM|Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining USBen_US
dc.relation.isversionofhttps://doi.org/10.1145/3534678.3539412en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceACM|Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining USBen_US
dc.titleFlexible Modeling and Multitask Learning using Differentiable Tree Ensemblesen_US
dc.typeArticleen_US
dc.identifier.citationIbrahim, Shibal, Hazimeh, Hussein and Mazumder, Rahul. 2022. "Flexible Modeling and Multitask Learning using Differentiable Tree Ensembles."
dc.contributor.departmentSloan School of Management
dc.contributor.departmentMassachusetts Institute of Technology. Operations Research Center
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.updated2022-11-03T01:12:13Z
dc.language.rfc3066en
dc.rights.holderThe author(s)
dspace.date.submission2022-11-03T01:12:13Z
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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