8 citations · 28 across the 7 of their papers we have counts for
7 papers
Algorithms for audio inpainting based on probabilistic nonnegative matrix factorization
Ondřej Mokrý, Paul Magron, Thomas Oberlin +1
Audio inpainting, i.e., the task of restoring missing or occluded audio signal samples, usually relies on sparse representations or autoregressive modeling. In this paper, we propo…
A majorization-minimization algorithm for nonnegative binary matrix factorization
Paul Magron, Cédric Févotte
This paper tackles the problem of decomposing binary data using matrix factorization. We consider the family of mean-parametrized Bernoulli models, a class of generative models tha…
Learning the Proximity Operator in Unfolded ADMM for Phase Retrieval
Pierre-Hugo Vial, Paul Magron, Thomas Oberlin +1
This paper considers the phase retrieval (PR) problem, which aims to reconstruct a signal from phaseless measurements such as magnitude or power spectrograms. PR is generally handl…
Accelerating Non-Negative and Bounded-Variable Linear Regression Algorithms with Safe Screening
Cassio F. Dantas, Emmanuel Soubies, Cédric Févotte
Non-negative and bounded-variable linear regression problems arise in a variety of applications in machine learning and signal processing. In this paper, we propose a technique to…
Leveraging Joint-Diagonalization in Transform-Learning NMF
Sixin Zhang, Emmanuel Soubies, Cédric Févotte
Non-negative matrix factorization with transform learning (TL-NMF) is a recent idea that aims at learning data representations suited to NMF. In this work, we relate TL-NMF to the…
Unbalanced Optimal Transport through Non-negative Penalized Linear Regression
Laetitia Chapel, Rémi Flamary, Haoran Wu +2
This paper addresses the problem of Unbalanced Optimal Transport (UOT) in which the marginal conditions are relaxed (using weighted penalties in lieu of equality) and no additional…