Privacy-preserving matrix factorization
Recommender systems typically require users to reveal their ratings to a recommender
service, which subsequently uses them to provide relevant recommendations. Revealing …
service, which subsequently uses them to provide relevant recommendations. Revealing …
[PDF][PDF] Privacy-Preserving Matrix Factorization
V Nikolaenko, S Ioannidis, U Weinsberg, M Joye, N Taft… - marcjoye.github.io
Recommender systems typically require users to reveal their ratings to a recommender
service, which subsequently uses them to provide relevant recommendations. Revealing …
service, which subsequently uses them to provide relevant recommendations. Revealing …
[PDF][PDF] Privacy-Preserving Matrix Factorization
V Nikolaenko, S Ioannidis, U Weinsberg, M Joye, N Taft… - 2013 - academia.edu
Recommender systems typically require users to reveal their ratings to a recommender
service, which subsequently uses them to provide relevant recommendations. Revealing …
service, which subsequently uses them to provide relevant recommendations. Revealing …
[PDF][PDF] Privacy-Preserving Matrix Factorization
V Nikolaenko, S Ioannidis, U Weinsberg, M Joye, N Taft… - 2013 - ece.neu.edu
Recommender systems typically require users to reveal their ratings to a recommender
service, which subsequently uses them to provide relevant recommendations. Revealing …
service, which subsequently uses them to provide relevant recommendations. Revealing …
Privacy Preserving Matrix Factorization
V Nikolaenko, S Ioannidis, U Weinsberg, M Joye, N Taft… - research.google
Recommender systems typically require users to reveal their ratings to a recommender
service, which subsequently uses them to provide relevant recommendations. Revealing …
service, which subsequently uses them to provide relevant recommendations. Revealing …
[PDF][PDF] Privacy-Preserving Matrix Factorization
V Nikolaenko, S Ioannidis, U Weinsberg, M Joye, N Taft… - 2013 - ece.neu.edu
Recommender systems typically require users to reveal their ratings to a recommender
service, which subsequently uses them to provide relevant recommendations. Revealing …
service, which subsequently uses them to provide relevant recommendations. Revealing …
[PDF][PDF] Privacy-Preserving Matrix Factorization
V Nikolaenko, S Ioannidis, U Weinsberg, M Joye, N Taft… - 2013 - Citeseer
Recommender systems typically require users to reveal their ratings to a recommender
service, which subsequently uses them to provide relevant recommendations. Revealing …
service, which subsequently uses them to provide relevant recommendations. Revealing …
[引用][C] Privacy-preserving matrix factorization
V Nikolaenko, S Ioannidis, U Weinsberg… - Proceedings of the …, 2013 - cir.nii.ac.jp
Privacy-preserving matrix factorization | CiNii Research CiNii 国立情報学研究所 学術情報
ナビゲータ[サイニィ] 詳細へ移動 検索フォームへ移動 論文・データをさがす 大学図書館の本を …
ナビゲータ[サイニィ] 詳細へ移動 検索フォームへ移動 論文・データをさがす 大学図書館の本を …
[PDF][PDF] Privacy-Preserving Matrix Factorization
V Nikolaenko, S Ioannidis, U Weinsberg, M Joye, N Taft… - 2013 - ece.northeastern.edu
Recommender systems typically require users to reveal their ratings to a recommender
service, which subsequently uses them to provide relevant recommendations. Revealing …
service, which subsequently uses them to provide relevant recommendations. Revealing …
[引用][C] Privacy Preserving Matrix Factorization
V Nikolaenko, S Ioannidis, U Weinsberg, M Joye, N Taft… - research.google
Privacy Preserving Matrix Factorization Jump to Content Research Research Who we are Back
to Who we are menu Defining the technology of today and tomorrow. Philosophy We strive to …
to Who we are menu Defining the technology of today and tomorrow. Philosophy We strive to …