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Obtaining Fairness using Optimal Transport Theory.

, , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 2357-2365. PMLR, (2019)

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Confidence Intervals for Testing Disparate Impact in Fair Learning., , , and . CoRR, (2018)optimalFlow: Optimal-transport approach to flow cytometry gating and population matching., , , , and . CoRR, (2019)Barycenter in Wasserstein Spaces: Existence and Consistency., and . GSI, volume 9389 of Lecture Notes in Computer Science, page 104-108. Springer, (2015)Are fairness metric scores enough to assess discrimination biases in machine learning?, , , and . CoRR, (2023)Dimension Reduction for time series with Variational AutoEncoders., , , and . CoRR, (2022)Multiple Testing for Outlier Detection in Space Telemetries., , , , and . IEEE Trans. Big Data, 6 (3): 443-451 (2020)Counterfactual Explanation for Multivariate Times Series Using A Contrastive Variational Autoencoder., , , and . ICASSP, page 1-5. IEEE, (2023)Achieving Robustness in Classification Using Optimal Transport With Hinge Regularization., , , , , and . CVPR, page 505-514. Computer Vision Foundation / IEEE, (2021)COCKATIEL: COntinuous Concept ranKed ATtribution with Interpretable ELements for explaining neural net classifiers on NLP., , , , , and . ACL (Findings), page 5120-5136. Association for Computational Linguistics, (2023)Breaking Bias: How Optimal Transport Can Help to Tackle Gender Biases in NLP Based Job Recommendation Systems?, , , , and . EWAF, volume 3442 of CEUR Workshop Proceedings, CEUR-WS.org, (2023)