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KDD
2009
ACM
298views Data Mining» more  KDD 2009»
14 years 2 months ago
Mind the gaps: weighting the unknown in large-scale one-class collaborative filtering
One-Class Collaborative Filtering (OCCF) is a task that naturally emerges in recommender system settings. Typical characteristics include: Only positive examples can be observed, ...
Rong Pan, Martin Scholz
CORR
2010
Springer
175views Education» more  CORR 2010»
13 years 8 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
2008
IEEE
14 years 8 months ago
Bayesian probabilistic matrix factorization using Markov chain Monte Carlo
Low-rank matrix approximation methods provide one of the simplest and most effective approaches to collaborative filtering. Such models are usually fitted to data by finding a MAP...
Ruslan Salakhutdinov, Andriy Mnih
ESANN
2007
13 years 9 months ago
Collaborative Filtering with interlaced Generalized Linear Models
Collaborative Filtering (CF) aims at finding patterns in a sparse matrix of contingency. It can be used for example to mine the ratings given by users on a set of items. In this p...
Nicolas Delannay, Michel Verleysen
JMLR
2010
156views more  JMLR 2010»
13 years 2 months ago
Collaborative Filtering on a Budget
Matrix factorization is a successful technique for building collaborative filtering systems. While it works well on a large range of problems, it is also known for requiring signi...
Alexandros Karatzoglou, Alexander J. Smola, Markus...