Several approaches to collaborative filtering have been studied but seldom have studies been reported for large (several million users and items) and dynamic (the underlying item ...
With the increasing popularity of recommender systems in commercial services, the quality of recommendations has increasingly become an important to study, much like the quality o...
Collaborative Filtering, considered by many researchers as the most important technique for information filtering, has been extensively studied by both academic and industrial co...
Collaborative filtering (CF) allows the preferences of multiple users to be pooled to make recommendations regarding unseen products. We consider in this paper the problem of onl...
Craig Boutilier, Richard S. Zemel, Benjamin M. Mar...
Multi-subject analysis of functional Magnetic Resonance Imaging (fMRI) data relies on within-subject studies, which are usually conducted using a massively univariate approach. In...
Philippe Ciuciu, Thomas Vincent, Anne-Laure Fouque...