Paula Gordaliza

According to our database, Paula Gordaliza authored at least 12 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Dancing in the Shadows: Harnessing Ambiguity for Fairer Classifiers.

Ainhize Barrainkua, Paula Gordaliza, José Antonio Lozano, Novi Quadrianto

CoRR, 2024

Uncertainty Matters: Stable Conclusions under Unstable Assessment of Fairness Results.

Ainhize Barrainkua, Paula Gordaliza, José Antonio Lozano, Novi Quadrianto

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

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, February, 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

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

Uncertainty in Fairness Assessment: Maintaining Stable Conclusions Despite Fluctuations.

Ainhize Barrainkua, Paula Gordaliza, José Antonio Lozano, Novi Quadrianto

CoRR, 2023

2022

A Survey on Preserving Fairness Guarantees in Changing Environments.

Ainhize Barrainkua, Paula Gordaliza, José Antonio Lozano, Novi Quadrianto

CoRR, 2022

2020

Review of Mathematical frameworks for Fairness in Machine Learning.

Eustasio del Barrio, Paula Gordaliza, Jean-Michel Loubes

CoRR, 2020

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

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

Obtaining Fairness using Optimal Transport Theory.

Paula Gordaliza, Eustasio del Barrio, Fabrice Gamboa, Jean-Michel Loubes

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Confidence Intervals for Testing Disparate Impact in Fair Learning.

Philippe C. Besse, Eustasio del Barrio, Paula Gordaliza, Jean-Michel Loubes

CoRR, 2018