11 citations · 11 across the 7 of their papers we have counts for
6 papers · 1 filter
Block Distributed Majorize-Minimize Memory Gradient Algorithm and its application to 3D image restoration
Mathieu Chalvidal, Emilie Chouzenoux
Modern 3D image recovery problems require powerful optimization frameworks to handle high dimensionality while providing reliable numerical solutions in a reasonable time. In this…
GraphEM: EM algorithm for blind Kalman filtering under graphical sparsity constraints
Émilie Chouzenoux, Víctor Elvira
Modeling and inference with multivariate sequences is central in a number of signal processing applications such as acoustics, social network analysis, biomedical, and finance, to…
SPOQ -Over- Regularization for Sparse Signal Recovery applied to Mass Spectrometry
Afef Cherni, Emilie Chouzenoux, Laurent Duval +1
Underdetermined or ill-posed inverse problems require additional information for \ldd{d} sound solutions with tractable optimization algorithms. Sparsity yields consequent heuristi…
General risk measures for robust machine learning
Emilie Chouzenoux, Henri Gérard, Jean-Christophe Pesquet
A wide array of machine learning problems are formulated as the minimization of the expectation of a convex loss function on some parameter space. Since the probability distributio…
Deep Unfolding of a Proximal Interior Point Method for Image Restoration
Carla Bertocchi, Emilie Chouzenoux, Marie-Caroline Corbineau +2
Variational methods are widely applied to ill-posed inverse problems for they have the ability to embed prior knowledge about the solution. However, the level of performance of the…
A probabilistic incremental proximal gradient method
Ömer Deniz Akyildiz, Émilie Chouzenoux, Víctor Elvira +1
In this paper, we propose a probabilistic optimization method, named probabilistic incremental proximal gradient (PIPG) method, by developing a probabilistic interpretation of the…