A federated learning method for privacy-preserving personalized recommendations



Title:	A federated learning method for privacy-preserving personalized recommendations En federerad maskininlärningsmetod för sekretessbevarande personifierade rekommendationer
Author(s):	Saxén, Daniel
Date:	2021-03-15
Language:	en
Pages:	50
Major/Subject:	Security and Cloud Computing (Security)
Degree programme:	Master’s Programme in Computer, Communication and Information Sciences
Supervising professor(s):	Lindqvist, Janne
Thesis advisor(s):	Flanagan, Adrian
Keywords:	AI, machine learning, federated learning, privacy-preserving, personalized advertising
Location:	Archive OEV
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Permanent link to this item: http://urn.fi/URN:NBN:fi:aalto-202103212410 Email this Export to RefWorks QR Code Print BibTex Tweet