1 citations · 1 across the 3 of their papers we have counts for
5 papers
Adaptive scaling of the learning rate by second order automatic differentiation
Frédéric de Gournay, Alban Gossard
In the context of the optimization of Deep Neural Networks, we propose to rescale the learning rate using a new technique of automatic differentiation. This technique relies on the…
Off-the-grid data-driven optimization of sampling schemes in MRI
Alban Gossard, Frédéric de Gournay, Pierre Weiss
We propose a novel learning based algorithm to generate efficient and physically plausible sampling patterns in MRI. This method has a few advantages compared to recent learning ba…
Approximation of curves with piecewise constant or piecewise linear functions
Frédéric de Gournay, Jonas Kahn, Léo Lebrat
In this paper we compute the Hausdorff distance between sets of continuous curves and sets of piecewise constant or linear discretizations. These sets are Sobolev balls given by th…
Convex Regularization and Representer Theorems
Claire Boyer, Antonin Chambolle, Yohann de Castro +3
We establish a result which states that regularizing an inverse problem with the gauge of a convex set yields solutions which are linear combinations of a few extreme points or…
On Representer Theorems and Convex Regularization
Claire Boyer, Antonin Chambolle, Yohann De Castro +3
We establish a general principle which states that regularizing an inverse problem with a convex function yields solutions which are convex combinations of a small number of atoms.…