Confidence Intervals for Testing Disparate Impact in Fair Learning. - Philippe C. Besse; Eustasio del Barrio; Paula Gordaliza; Jean-Michel Loubes (CoRR, 2018)

Obtaining Fairness using Optimal Transport Theory. - Paula Gordaliza; Eustasio del Barrio; Fabrice Gamboa; Jean-Michel Loubes (ICML, 2019)

Central limit theorem and bootstrap procedure for Wasserstein's variations with an application to structural relationships between distributions. - Eustasio del Barrio; Paula Gordaliza; Hélène Lescornel; Jean-Michel Loubes (J. Multivar. Anal., 2019)

A survey of bias in Machine Learning through the prism of Statistical Parity for the Adult Data Set. - Philippe C. Besse; Eustasio del Barrio; Paula Gordaliza; Jean-Michel Loubes; Laurent Risser (CoRR, 2020)

Review of Mathematical frameworks for Fairness in Machine Learning. - Eustasio del Barrio; Paula Gordaliza; Jean-Michel Loubes (CoRR, 2020)

A Survey on Preserving Fairness Guarantees in Changing Environments. - Ainhize Barrainkua; Paula Gordaliza; José Antonio Lozano 001; Novi Quadrianto (CoRR, 2022)

Uncertainty in Fairness Assessment: Maintaining Stable Conclusions Despite Fluctuations. - Ainhize Barrainkua; Paula Gordaliza; José Antonio Lozano 001; Novi Quadrianto (CoRR, 2023)

A study on group fairness in healthcare outcomes for nursing home residents during the COVID-19 pandemic in the Basque Country. - Hristo Inouzhe; Irantzu Barrio; Paula Gordaliza; María Xosé Rodríguez-Álvarez; Itxaso Bengoechea; José María Quintana (CoRR, 2023)

Fair Kernel Regression through Cross-Covariance Operators. - Adrian Perez-Suay; Paula Gordaliza; Jean-Michel Loubes; Dino Sejdinovic; Gustau Camps-Valls (Trans. Mach. Learn. Res., 2023)

Interaction with a Hand Rehabilitation Exoskeleton in EMG-Driven Bilateral Therapy: Influence of Visual Biofeedback on the Users' Performance. - Ana Cisnal; Paula Gordaliza; Javier Pérez Turiel; Juan C. Fraile (Sensors, 2023)

Uncertainty Matters: Stable Conclusions under Unstable Assessment of Fairness Results. - Ainhize Barrainkua; Paula Gordaliza; José Antonio Lozano 001; Novi Quadrianto (AISTATS, 2024)

Dancing in the Shadows: Harnessing Ambiguity for Fairer Classifiers. - Ainhize Barrainkua; Paula Gordaliza; José Antonio Lozano 001; Novi Quadrianto (CoRR, 2024)

PLS-based approach for fair representation learning. - Elena M. De-Diego; Adrián Pérez-Suay; Paula Gordaliza; Jean-Michel Loubes (CoRR, 2025)

Preserving the Fairness Guarantees of Classifiers in Changing Environments: A Survey. - Ainhize Barrainkua; Paula Gordaliza; José Antonio Lozano 001; Novi Quadrianto (ACM Comput. Surv., 2025)