Abstract. We present a Bayesian treatment of non-negative matrix factorization (NMF), based on a normal likelihood and exponential priors, and derive an efficient Gibbs sampler to ...
Data sparsity, scalability and prediction quality have been recognized as the three most crucial challenges that every collaborative filtering algorithm or recommender system conf...
This article presents a new method for discovering hidden patterns in high-dimensional dataset resulting from image registration. It is based on true factor analysis, a statistica...
Collaborative Filtering, considered by many researchers as the most important technique for information filtering, has been extensively studied by both academic and industrial co...
This paper introduces a novel algorithm for the nonnegative matrix factorization and completion problem, which aims to find nonnegative matrices X and Y from a subset of entries o...