2 citations · 3 across the 6 of their papers we have counts for
12 papers
A novel multi-scale loss function for classification problems in machine learning
Leonid Berlyand, Robert Creese, Pierre-Emmanuel Jabin
We introduce two-scale loss functions for use in various gradient descent algorithms applied to classification problems via deep neural networks. This new method is generic in the…
Entropy dissipation and propagation of chaos for the uniform reshuffling model
Fei Cao, Pierre-Emmanuel Jabin, Sebastien Motsch
We investigate the uniform reshuffling model for money exchanges: two agents picked uniformly at random redistribute their dollars between them. This stochastic dynamics is of mean…
Mean-field limit and quantitative estimates with singular attractive kernels
Didier Bresch, Pierre-Emmanuel Jabin, Zhenfu Wang
This paper proves the mean field limit and quantitative estimates for many-particle systems with singular attractive interactions between particles. As an important example, a full…
Stability for the Training of Deep Neural Networks and Other Classifiers
Leonid Berlyand, Pierre-Emmanuel Jabin, C. Alex Safsten
We examine the stability of loss-minimizing training processes that are used for deep neural networks (DNN) and other classifiers. While a classifier is optimized during training t…
Modulated Free Energy and Mean Field Limit
Didier Bresch, Pierre-Emmanuel Jabin, Zhenfu Wang
This is the document corresponding to the talk the first author gave at IH{É}S for the Laurent Schwartz seminar on November 19, 2019. It concerns our recent introduction of a modul…
Local regularity result for an optimal transportation problem with rough measures in the plane
P. -E. Jabin, A. Mellet, M. Molina
We investigate the properties of convex functions in the plane that satisfy a local inequality which generalizes the notion of sub-solution of Monge-Ampere equation for a Monge-Kan…