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Towards privacy-preserving mobile applications with federated learning: The case of matrix factorization (poster)

dc.contributor.authorDolui, Koustabh
dc.contributor.authorGyllensten, Illapha Cuba
dc.contributor.authorLowet, Dietwig
dc.contributor.authorMichiels, Sam
dc.contributor.authorHallez, Hans
dc.contributor.authorHughes, Danny
dc.date.accessioned2021-10-27T08:55:50Z
dc.date.available2021-10-27T08:55:50Z
dc.date.issued2019
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/32911
dc.sourceIIOimport
dc.titleTowards privacy-preserving mobile applications with federated learning: The case of matrix factorization (poster)
dc.typeProceedings paper
dc.date.embargo9999-12-31
dc.source.peerreviewyes
dc.source.beginpage624
dc.source.endpage625
dc.source.conferenceMobiSys '19: Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services
dc.source.conferencedate17/06/2019
dc.source.conferencelocationSeoul Korea
dc.identifier.urlhttps://doi.org/10.1145/3307334.3328657
imec.availabilityPublished - open access


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