no code implementations • 20 Jun 2022 • Loucas Pillaud-Vivien, Julien Reygner, Nicolas Flammarion
Understanding the implicit bias of training algorithms is of crucial importance in order to explain the success of overparametrised neural networks.
no code implementations • 28 Jan 2021 • Tony Lelièvre, Mouad Ramil, Julien Reygner
Consider the Langevin process, described by a vector (position, momentum) in $\mathbb{R}^{d}\times\mathbb{R}^d$.
Probability Spectral Theory
no code implementations • 19 Oct 2020 • Julien Reygner, Adrien Touboul
We study an optimal reweighting that minimizes the Wasserstein distance between the empirical measures of the two samples, and leads to an expression of the weights in terms of Nearest Neighbors.