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ICML
2004
IEEE
14 years 5 months ago
The multiple multiplicative factor model for collaborative filtering
We describe a class of causal, discrete latent variable models called Multiple Multiplicative Factor models (MMFs). A data vector is represented in the latent space as a vector of...
Benjamin M. Marlin, Richard S. Zemel
KDD
2007
ACM
191views Data Mining» more  KDD 2007»
14 years 5 months ago
Modeling relationships at multiple scales to improve accuracy of large recommender systems
The collaborative filtering approach to recommender systems predicts user preferences for products or services by learning past useritem relationships. In this work, we propose no...
Robert M. Bell, Yehuda Koren, Chris Volinsky
SIGIR
2011
ACM
12 years 7 months ago
Collaborative competitive filtering: learning recommender using context of user choice
While a user’s preference is directly reflected in the interactive choice process between her and the recommender, this wealth of information was not fully exploited for learni...
Shuang-Hong Yang, Bo Long, Alexander J. Smola, Hon...
CORR
2010
Springer
175views Education» more  CORR 2010»
13 years 5 months ago
Incorporating Side Information in Probabilistic Matrix Factorization with Gaussian Processes
Probabilistic matrix factorization (PMF) is a powerful method for modeling data associated with pairwise relationships, finding use in collaborative filtering, computational biolo...
Ryan Prescott Adams, George E. Dahl, Iain Murray
ICML
2007
IEEE
14 years 5 months ago
Restricted Boltzmann machines for collaborative filtering
Most of the existing approaches to collaborative filtering cannot handle very large data sets. In this paper we show how a class of two-layer undirected graphical models, called R...
Ruslan Salakhutdinov, Andriy Mnih, Geoffrey E. Hin...