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dc.contributor.authorMasegosa, Andres
dc.contributor.authorMartinez, Ana M.
dc.contributor.authorRamos-López, Dario
dc.contributor.authorCabañas, Rafael
dc.contributor.authorLangseth, Helge
dc.contributor.authorNielsen, Thomas D.
dc.contributor.authorMadsen, Anders L.
dc.date.accessioned2019-04-30T07:24:59Z
dc.date.available2019-04-30T07:24:59Z
dc.date.created2018-10-08T09:02:05Z
dc.date.issued2018
dc.identifier.issn0950-7051
dc.identifier.urihttp://hdl.handle.net/11250/2596031
dc.description.abstractThe AMIDST Toolbox is an open source Java software for scalable probabilistic machine learning with a special focus on (massive) streaming data. The toolbox supports a flexible modelling language based on probabilistic graphical models with latent variables. AMIDST provides parallel and distributed implementations of scalable algorithms for doing probabilistic inference and Bayesian parameter learning in the specified models. These algorithms are based on a flexible variational message passing scheme, which supports discrete and continuous variables from a wide range of probability distributions.nb_NO
dc.language.isoengnb_NO
dc.publisherElseviernb_NO
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.titleAMIDST: A Java toolbox for scalable probabilistic machine learningnb_NO
dc.title.alternativeAMIDST: A Java toolbox for scalable probabilistic machine learningnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersionnb_NO
dc.source.volume163nb_NO
dc.source.journalKnowledge-Based Systemsnb_NO
dc.identifier.doi10.1016/j.knosys.2018.09.019
dc.identifier.cristin1618562
dc.relation.projectEC/FP7/619209nb_NO
dc.description.localcode© 2018. This is the authors’ accepted and refereed manuscript to the article. Locked until 29.9.2020 due to copyright restrictions. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/nb_NO
cristin.unitcode194,63,10,0
cristin.unitnameInstitutt for datateknologi og informatikk
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
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