Probabilistic Matrix Factorization
Probabilistic Matrix Factorization is a probabilistic graphical model for collaborative filtering that factorizes a user-item interaction matrix into latent user and item feature matrices under Gaussian observation noise, distinguishing it from deterministic matrix factorization methods by modeling uncertainty in predictions through a probabilistic likelihood framework.
273
Publications
22.9K
Citations
796
Authors
336
Institutions
Publications per year
2017–2026
113
273
Probabilistic Matrix Factorization
Andriy Mnih, Ruslan Salakhutdinov · Neural Information Processing Systems · 2007 · 3.6K citations
Hao Ma, Haixuan Yang, Michael R. Lyu et al. · 2008 · 1.4K citations
Probabilistic Matrix Factorization
2007 · 1.1K citations
Convolutional Matrix Factorization for Document Context-Aware Recommendation
Chanyoung Park, Jinoh Oh, Sungyoung Lee et al. · 2016 · 779 citations
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336
Chinese University of Hong Kong
Hong Kong, Hong Kong
9 h-index
33 publications
7.7K citations
Rutgers, The State University of New Jersey
New Brunswick, United States
8 h-index
12 publications
562 citations
Tsinghua University
Beijing, China
8 h-index
28 publications
2.6K citations

Chinese Academy of Sciences
Beijing, China
7 h-index
20 publications
599 citations

University of Toronto
Toronto, Canada
6 h-index
13 publications
10.6K citations
Carnegie Mellon University
Pittsburgh, United States
6 h-index
11 publications
765 citations

Beijing University of Posts and Telecommunications
Beijing, China
5 h-index
21 publications
1.2K citations

Zhejiang University
Hangzhou, China
5 h-index
16 publications
860 citations
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11 publications · 419 citations
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Repository · 13 publications · 497 citations
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10 publications · 367 citations
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9 publications · 690 citations
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Conference · 9 publications · 506 citations
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