In this short paper we propose an alternative, user-centric, privacy enhanced, decentralised approach to MF. Our method pushes the computation of the ...
PDMFRec: A Decentralised Matrix Factorisation with Tunable User ... Here we demonstrate the behaviour of PDMFRec under different user-set privacy.
This approach introduces an increased risk when it comes to user privacy. In this short paper we propose an alternative, user-centric, privacy enhanced, ...
This short paper proposes an alternative, user-centric, privacy enhanced, decentralised approach to matrix factorisation, which pushes the computation of ...
Duriakova et al. [26] proposed a decentralized distributed matrix factorization framework (PDMFRec) where users can autonomously adjust their privacy levels, ...
Apr 30, 2020 · In this short paper we propose an alternative, user-centric, privacy enhanced, decentralised approach to MF. Our method pushes the computation ...
ABSTRACT. Conventional approaches to matrix factorisation (MF) typically rely on a centralised collection of user data for building a MF model. This.
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Co-authors ; PDMFRec: a decentralised matrix factorisation with tunable user-centric privacy. E Duriakova, EZ Tragos, B Smyth, N Hurley, FJ Peña, P Symeonidis, .
PDMFRec: A Decentralised Matrix Factorisation with Tunable User-centric Privacy. (ACM, 2019-09-19). Duriakova, Erika. ;. Tragos, Elias. ;. Smyth, Barry. ;.