dc.contributor.author | Masegosa, Andres | |
dc.contributor.author | Martinez, Ana M. | |
dc.contributor.author | Ramos-López, Dario | |
dc.contributor.author | Cabañas, Rafael | |
dc.contributor.author | Langseth, Helge | |
dc.contributor.author | Nielsen, Thomas D. | |
dc.contributor.author | Madsen, Anders L. | |
dc.date.accessioned | 2019-04-30T07:24:59Z | |
dc.date.available | 2019-04-30T07:24:59Z | |
dc.date.created | 2018-10-08T09:02:05Z | |
dc.date.issued | 2018 | |
dc.identifier.issn | 0950-7051 | |
dc.identifier.uri | http://hdl.handle.net/11250/2596031 | |
dc.description.abstract | The 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.iso | eng | nb_NO |
dc.publisher | Elsevier | nb_NO |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/deed.no | * |
dc.title | AMIDST: A Java toolbox for scalable probabilistic machine learning | nb_NO |
dc.title.alternative | AMIDST: A Java toolbox for scalable probabilistic machine learning | nb_NO |
dc.type | Journal article | nb_NO |
dc.type | Peer reviewed | nb_NO |
dc.description.version | acceptedVersion | nb_NO |
dc.source.volume | 163 | nb_NO |
dc.source.journal | Knowledge-Based Systems | nb_NO |
dc.identifier.doi | 10.1016/j.knosys.2018.09.019 | |
dc.identifier.cristin | 1618562 | |
dc.relation.project | EC/FP7/619209 | nb_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.unitcode | 194,63,10,0 | |
cristin.unitname | Institutt for datateknologi og informatikk | |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |