153 citations · 628 across the 41 of their papers we have counts for
19 papers · 1 filter
Stability Bounds for the Unfolded Forward-Backward Algorithm
Emilie Chouzenoux, Cecile Della Valle, Jean-Christophe Pesquet
We consider a neural network architecture designed to solve inverse problems where the degradation operator is linear and known. This architecture is constructed by unrolling a for…
An Effective Iterative Solution for Independent Vector Analysis with Convergence Guarantees
Clément Cosserat, Ben Gabrielson, Emilie Chouzenoux +2
Independent vector analysis (IVA) is an attractive solution to address the problem of joint blind source separation (JBSS), that is, the simultaneous extraction of latent sources f…
Solution of Mismatched Monotone+Lipschitz Inclusion Problems
Emilie Chouzenoux, Jean-Christophe Pesquet, Fernando Roldán
In this article, we study the convergence of algorithms for solving monotone inclusions in the presence of adjoint mismatch. The adjoint mismatch arises when the adjoint of a linea…
A new non-convex framework to improve asymptotical knowledge on generic stochastic gradient descent
Jean-Baptiste Fest, Audrey Repetti, Emilie Chouzenoux
Stochastic gradient optimization methods are broadly used to minimize non-convex smooth objective functions, for instance when training deep neural networks. However, theoretical g…
A stochastic use of the Kurdyka-Lojasiewicz property: Investigation of optimization algorithms behaviours in a non-convex differentiable framework
Jean-Baptiste Fest, Audrey Repetti, Emilie Chouzenoux
Stochastic differentiable approximation schemes are widely used for solving high dimensional problems. Most of existing methods satisfy some desirable properties, including conditi…
Inversion of Integral Models: a Neural Network Approach
Emilie Chouzenoux, Cecile Della Valle, Jean-Christophe Pesquet
We introduce a neural network architecture to solve inverse problems linked to a one-dimensional integral operator. This architecture is built by unfolding a forward-backward algor…