Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Ferdinand Genans5 · h 1
- Olivier Wintenberger5 · h 19
- Sylvain Le Corff4 · h 4
- Stanislas Strasman2 profiles3 · h 2
- Antoine Godichon-Baggioni2 · h 2
- Antonio Ocello2 · h 3
- Claire Boyer2 profiles2 · h 6
- François-Xavier Vialard2 · h 25
- Jordan Serres2 · h 3
- Pierre Gaillard2 profiles2 · h 4
- Vincent Lemaire2 · h 2
- Alexandre Delplanque1 · h 1
- Laboratoire de Probabilités et Modèles AléatoiresFR9 papers
- Laboratoire de Probabilités, Statistique et ModélisationFR9 papers
- Sorbonne UniversitéFR9 papers
- Centre de Mathématiques Appliquées de l'École polytechniqueFR2 papers
- École PolytechniqueFR2 papers
- Institut Universitaire de FranceFR2 papers
- Laboratoire de Mathématiques d'OrsayFR2 papers
- Laboratoire d'Informatique Gaspard-MongeFR2 papers
- Université Paris-SaclayFR2 papers
- Centre Inria de SaclayFR1 paper
- Centre Inria d'Université Côte d'AzurFR1 paper
- Centre National de la Recherche ScientifiqueFR1 paper
5 papers · 1 filter
A Generalization of Caffarelli's Contraction Theorem to Nearly Spherical Manifolds
Yuxin Ge, Jordan Serres
We show that every nearly spherical manifold can be realized as the volume-preserving image of a round sphere, via the Brenier-McCann optimal transport map. This theorem extends Ca…
Decreasing Entropic Regularization Averaged Gradient for Semi-Discrete Optimal Transport
Ferdinand Genans, Antoine Godichon-Baggioni, François-Xavier Vialard +1
Adding entropic regularization to Optimal Transport (OT) problems has become a standard approach for designing efficient and scalable solvers. However, regularization introduces a…
Stochastic Optimization in Semi-Discrete Optimal Transport: Convergence Analysis and Minimax Rate
Ferdinand Genans, Antoine Godichon-Baggioni, François-Xavier Vialard +1
We investigate the semi-discrete Optimal Transport (OT) problem, where a continuous source measure is transported to a discrete target measure , with particular attention to…
Attention-based clustering
Rodrigo Maulen-Soto, Pierre Marion, Claire Boyer
Transformers have emerged as a powerful neural network architecture capable of tackling a wide range of learning tasks. In this work, we provide a theoretical analysis of their abi…
Transductive Conformal Inference for Full Ranking
Jean-Baptiste Fermanian, Pierre Humbert, Gilles Blanchard
We introduce a method based on Conformal Prediction (CP) to quantify the uncertainty of full ranking algorithms. We focus on a specific scenario where items are to be ranked…