One-Class Collaborative Filtering (OCCF) is a task that naturally emerges in recommender system settings. Typical characteristics include: Only positive examples can be observed, ...
Probabilistic matrix factorization (PMF) is a powerful method for modeling data associated with pairwise relationships, finding use in collaborative filtering, computational biolo...
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...
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...
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...