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

dc.contributor.author	Dolui, Koustabh
dc.contributor.author	Gyllensten, Illapha Cuba
dc.contributor.author	Lowet, Dietwig
dc.contributor.author	Michiels, Sam
dc.contributor.author	Hallez, Hans
dc.contributor.author	Hughes, Danny
dc.date.accessioned	2021-10-27T08:55:50Z
dc.date.available	2021-10-27T08:55:50Z
dc.date.embargo	9999-12-31
dc.date.issued	2019
dc.identifier.uri	https://imec-publications.be/handle/20.500.12860/32911
dc.identifier.url	https://doi.org/10.1145/3307334.3328657
dc.source.beginpage	624
dc.source.conference	MobiSys '19: Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services
dc.source.conferencedate	17/06/2019
dc.source.conferencelocation	Seoul Korea
dc.source.endpage	625
dc.title	Towards privacy-preserving mobile applications with federated learning: The case of matrix factorization (poster)
dc.type	Proceedings paper
dspace.entity.type	Publication
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