A Robust Convex Formulation for Ensemble Clustering

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorGao, Junningen_US
dc.contributor.authorYamada, Makotoen_US
dc.contributor.authorKaski, Samuelen_US
dc.contributor.authorMamitsuka, Hiroshien_US
dc.contributor.authorZhu, Shanfengen_US
dc.contributor.departmentDepartment of Computer Scienceen
dc.contributor.editorKambhampati, Subbaraoen_US
dc.contributor.groupauthorCentre of Excellence in Computational Inference, COINen
dc.contributor.groupauthorProfessorship Kaski Samuelen
dc.contributor.organizationFudan Universityen_US
dc.contributor.organizationKyoto Universityen_US
dc.date.accessioned2016-10-13T06:10:08Z
dc.date.issued2016-07en_US
dc.description.abstractWe formulate ensemble clustering as a regularization problem over nuclear norm and cluster-wise group norm, and present an efficient optimization algorithm, which we call Robust Convex Ensemble Clustering (RCEC). A key feature of RCEC allows to remove anomalous cluster assignments obtained from component clustering methods by using the group-norm regularization. Moreover, the proposed method is convex and can find the globally optimal solution. We first showed that using synthetic data experiments, RCEC could learn stable cluster assignments from the input matrix including anomalous clusters. We then showed that RCEC outperformed state-of-the-art ensemble clustering methods by using real-world data sets.en
dc.description.versionPeer revieweden
dc.format.extent6
dc.format.extent1476-1482
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationGao, J, Yamada, M, Kaski, S, Mamitsuka, H & Zhu, S 2016, A Robust Convex Formulation for Ensemble Clustering . in S Kambhampati (ed.), Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI-16) . AAAI Press, 2275 East Bayshore Road, Suite 160, Palo Alto CA 94303 USA, pp. 1476-1482, International Joint Conference on Artificial Intelligence, New York, New York, United States, 09/07/2016 . < http://www.ijcai.org/Proceedings/16/Papers/212.pdf >en
dc.identifier.isbn978-1-57735-770-4
dc.identifier.otherPURE UUID: 90901dfe-0a20-4f23-8bdf-1a89e1b054b2en_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/90901dfe-0a20-4f23-8bdf-1a89e1b054b2en_US
dc.identifier.otherPURE LINK: http://www.ijcai.org/Proceedings/16/Papers/212.pdfen_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/11509463/212.pdfen_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/22920
dc.identifier.urnURN:NBN:fi:aalto-201610135020
dc.language.isoenen
dc.relation.ispartofInternational Joint Conference on Artificial Intelligenceen
dc.relation.ispartofseriesProceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI-16)en
dc.rightsopenAccessen
dc.subject.keywordensemble clusteringen_US
dc.subject.keywordconvex optimizationen_US
dc.titleA Robust Convex Formulation for Ensemble Clusteringen
dc.typeA4 Artikkeli konferenssijulkaisussafi

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