8 citations · 8 across the 2 of their papers we have counts for
5 papers · 1 filter
Adversarially-Trained Nonnegative Matrix Factorization
Ting Cai, Vincent Y. F. Tan, Cédric Févotte
We consider an adversarially-trained version of the nonnegative matrix factorization, a popular latent dimensionality reduction technique. In our formulation, an attacker adds an a…
Second-order step-size tuning of SGD for non-convex optimization
Camille Castera, Jérôme Bolte, Cédric Févotte +1
In view of a direct and simple improvement of vanilla SGD, this paper presents a fine-tuning of its step-sizes in the mini-batch case. For doing so, one estimates curvature, based…
Expanding boundaries of Gap Safe screening
Cassio F. Dantas, Emmanuel Soubies, Cédric Févotte
Sparse optimization problems are ubiquitous in many fields such as statistics, signal/image processing and machine learning. This has led to the birth of many iterative algorithms…
Ordinal Non-negative Matrix Factorization for Recommendation
Olivier Gouvert, Thomas Oberlin, Cédric Févotte
We introduce a new non-negative matrix factorization (NMF) method for ordinal data, called OrdNMF. Ordinal data are categorical data which exhibit a natural ordering between the ca…
Nonnegative Matrix Factorization with Transform Learning
Dylan Fagot, Cédric Févotte, Herwig Wendt
Traditional NMF-based signal decomposition relies on the factorization of spectral data, which is typically computed by means of short-time frequency transform. In this paper we pr…