22 citations · 26 across the 9 of their papers we have counts for
9 papers
Irrationality as a mean of regularization in Bayesian Persuasion
Romain Duboscq, Frédéric de Gournay
We study a regularized variant of the Bayesian Persuasion problem, where the receiver's decision process includes a divergence-based penalty that accounts for deviations from perfe…
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…
3/4-discrete optimal transport
Frédéric de Gournay, Jonas Kahn, Léo Lebrat
This paper deals with the 3/4-discrete 2-Wasserstein optimal transport between two measures, where one is supported by a set of segment and the other one is supported by a set of D…
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.…
Optimal Transport Approximation of 2-Dimensional Measures
Frédéric de Gournay, Jonas Kahn, Léo Lebrat +1
We propose a fast and scalable algorithm to project a given density on a set of structured measures defined over a compact 2D domain. The measures can be discrete or supported on c…
Differentiation and regularity of semi-discrete optimal transport with respect to the parameters of the discrete measure
Frédéric de Gournay, Jonas Kahn, Léo Lebrat
This paper aims at determining under which conditions the semi-discrete optimal transport is twice differentiable with respect to the parameters of the discrete measure and exhibit…