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20172022
most citedReview of Mathematical frameworks for Fairness in Machine Learning

20 citations · 59 across the 8 of their papers we have counts for

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7 papers · 1 filter

math.ST20225 cited

An improved central limit theorem and fast convergence rates for entropic transportation costs

Eustasio del Barrio, Alberto Gonzalez-Sanz, Jean-Michel Loubes +1

We prove a central limit theorem for the entropic transportation cost between subgaussian probability measures, centered at the population cost. This is the first result which allo…

math.ST202112 cited

Central Limit Theorems for General Transportation Costs

Eustasio del Barrio, Alberto González-Sanz, Jean-Michel Loubes

We consider the problem of optimal transportation with general cost between a empirical measure and a general target probability on R d , with d 1. We extend results in [19]…

math.ST202010 cited

The statistical effect of entropic regularization in optimal transportation

Eustasio del Barrio, Jean-Michel Loubes

We propose to tackle the problem of understanding the effect of regularization in Sinkhorn algotihms. In the case of Gaussian distributions we provide a closed form for the regular…

math.ST20192 cited

A note on the Regularity of Center-Outward Distribution and Quantile Functions

Eustasio del Barrio, Alberto González-Sanz, Marc Hallin

We provide sufficient conditions under which the center-outward distribution and quantile functions introduced in Chernozhukov et al.~(2017) and Hallin~(2017) are homeomorphisms, t…

math.ST2019

On approximate validation of models: A Kolmogorov-Smirnov based approach

Eustasio del Barrio, Hristo Inouzhe, Carlos Matrán

Classical tests of fit typically reject a model for large enough real data samples. In contrast, often in statistical practice a model offers a good description of the data even th…

math.ST2018

A Central Limit Theorem for transportation cost with applications to Fairness Assessment in Machine Learning

Eustasio del Barrio, Paula Gordaliza, Jean-Michel Loubes

We provide a Central Limit Theorem for the Monge-Kantorovich distance between two empirical distributions with size and , for for observations on the re…