213 citations · 326 across the 14 of their papers we have counts for
16 papers
Majorization-minimization for Sparse Nonnegative Matrix Factorization with the -divergence
Arthur Marmin, José Henrique de Morais Goulart, Cédric Févotte
This article introduces new multiplicative updates for nonnegative matrix factorization with the -divergence and sparse regularization of one of the two factors (say, the activa…
A Comparative Study of Gamma Markov Chains for Temporal Non-Negative Matrix Factorization
Louis Filstroff, Olivier Gouvert, Cédric Févotte +1
Non-negative matrix factorization (NMF) has become a well-established class of methods for the analysis of non-negative data. In particular, a lot of effort has been devoted to pro…
Recommendation from Raw Data with Adaptive Compound Poisson Factorization
Olivier Gouvert, Thomas Oberlin, Cédric Févotte
Count data are often used in recommender systems: they are widespread (song play counts, product purchases, clicks on web pages) and can reveal user preference without any explicit…
An Inertial Newton Algorithm for Deep Learning
Camille Castera, Jérôme Bolte, Cédric Févotte +1
We introduce a new second-order inertial optimization method for machine learning called INNA. It exploits the geometry of the loss function while only requiring stochastic approxi…
A Ranking Model Motivated by Nonnegative Matrix Factorization with Applications to Tennis Tournaments
Rui Xia, Vincent Y. F. Tan, Louis Filstroff +1
We propose a novel ranking model that combines the Bradley-Terry-Luce probability model with a nonnegative matrix factorization framework to model and uncover the presence of laten…
Bayesian Mean-parameterized Nonnegative Binary Matrix Factorization
Alberto Lumbreras, Louis Filstroff, Cédric Févotte
Binary data matrices can represent many types of data such as social networks, votes, or gene expression. In some cases, the analysis of binary matrices can be tackled with nonnega…