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MFITS: Bayesian active learning with support for continuous fidelity parameters and variable cost

dc.contributor.authorKnudde, Nicolas
dc.contributor.authorCouckuyt, Ivo
dc.contributor.authorDhaene, Tom
dc.date.accessioned2021-10-27T11:35:00Z
dc.date.available2021-10-27T11:35:00Z
dc.date.issued2019
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/33307
dc.sourceIIOimport
dc.titleMFITS: Bayesian active learning with support for continuous fidelity parameters and variable cost
dc.typeProceedings paper
dc.contributor.imecauthorKnudde, Nicolas
dc.contributor.imecauthorCouckuyt, Ivo
dc.contributor.imecauthorDhaene, Tom
dc.contributor.orcidimecCouckuyt, Ivo::0000-0002-9524-4205
dc.contributor.orcidimecDhaene, Tom::0000-0003-2899-4636
dc.date.embargo9999-12-31
dc.source.peerreviewyes
dc.source.beginpage1
dc.source.endpage8
dc.source.conference6th ICML Workshop on Automated Machine Learning
dc.source.conferencedate9/06/2019
dc.source.conferencelocationLong Beach, CA USA
imec.availabilityPublished - open access


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