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dc.contributor.authorHoang, Trong Nghia
dc.contributor.authorLam, Chi Thanh
dc.contributor.authorLow, Bryan Kian Hsiang
dc.contributor.authorJaillet, Patrick
dc.date.accessioned2022-07-12T17:38:20Z
dc.date.available2022-07-12T17:38:20Z
dc.date.issued2020
dc.identifier.urihttps://hdl.handle.net/1721.1/143687
dc.language.isoen
dc.relation.isversionofhttps://proceedings.mlr.press/v119/hoang20b.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.titleLearning Task-Agnostic Embedding of Multiple Black-Box Experts for Multi-Task Model Fusionen_US
dc.typeArticleen_US
dc.identifier.citationHoang, Trong Nghia, Lam, Chi Thanh, Low, Bryan Kian Hsiang and Jaillet, Patrick. 2020. "Learning Task-Agnostic Embedding of Multiple Black-Box Experts for Multi-Task Model Fusion." INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 119, 119.
dc.contributor.departmentMIT-IBM Watson AI Lab
dc.contributor.departmentSloan School of Management
dc.relation.journalINTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 119en_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.updated2022-07-12T17:31:53Z
dspace.orderedauthorsHoang, TN; Lam, CT; Low, BKH; Jaillet, Pen_US
dspace.date.submission2022-07-12T17:31:55Z
mit.journal.volume119en_US
mit.licensePUBLISHER_POLICY
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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