213 citations · 326 across the 14 of their papers we have counts for
3 papers · 1 filter
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…