Paula Gordaliza
Paula Gordaliza
Adresse e-mail validée de math.univ-toulouse.fr
Titre
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Année
Obtaining fairness using optimal transport theory
E Del Barrio, F Gamboa, P Gordaliza, JM Loubes
arXiv preprint arXiv:1806.03195, 2018
63*2018
Central limit theorem and bootstrap procedure for Wasserstein’s variations with an application to structural relationships between distributions
E Del Barrio, P Gordaliza, H Lescornel, JM Loubes
Journal of Multivariate Analysis 169, 341-362, 2019
122019
A central limit theorem for Lp transportation cost on the real line with application to fairness assessment in machine learning
E Del Barrio, P Gordaliza, JM Loubes
Information and Inference: A Journal of the IMA 8 (4), 817-849, 2019
112019
Review of mathematical frameworks for fairness in machine learning
E del Barrio, P Gordaliza, JM Loubes
arXiv preprint arXiv:2005.13755, 2020
102020
A survey of bias in Machine Learning through the prism of Statistical Parity for the Adult Data Set
P Besse, E del Barrio, P Gordaliza, JM Loubes, L Risser
arXiv preprint arXiv:2003.14263, 2020
82020
Confidence intervals for testing disparate impact in fair learning
P Besse, E del Barrio, P Gordaliza, JM Loubes
arXiv preprint arXiv:1807.06362, 2018
62018
Airports: Análisis de eficiencia operacional basado en trayectorias de vuelo
A Alonso-Isla, MA Martınez Prieto, A Bregón Bregón, I Garcıa Miranda, ...
URL: https://biblioteca. sistedes. es/submissions/descargas/2018/JISBD/2018 …, 2017
32017
Fair learning: une approche basée sur le transport optimale
P Gordaliza Pastor
Université de Toulouse, Université Toulouse III-Paul Sabatier, 2020
2020
Clasificación no supervisada de datos funcionales: una aplicación a la clasificación con datos de navegación aérea
P Gordaliza Pastor
2017
Baricentros en el espacio de Wasserstein: aplicación a modelos estadísticos de deformación
P Gordaliza Pastor
2016
Application du Transport Optimal en Fair Learning
P Gordaliza, E del Barrio, JM Loubes
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