Jean-Michel Loubes
Orcid: 0000-0002-1252-2960
According to our database1,
Jean-Michel Loubes
authored at least 66 papers
between 2009 and 2025.
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Bibliography
2025
CoRR, February, 2025
2024
2023
Attraction-repulsion clustering: a way of promoting diversity linked to demographic parity in fair clustering.
Adv. Data Anal. Classif., December, 2023
An Improved Central Limit Theorem and Fast Convergence Rates for Entropic Transportation Costs.
SIAM J. Math. Data Sci., September, 2023
SIAM J. Imaging Sci., March, 2023
How Optimal Transport Can Tackle Gender Biases in Multi-Class Neural Network Classifiers for Job Recommendations.
Algorithms, March, 2023
Trans. Mach. Learn. Res., 2023
Are fairness metric scores enough to assess discrimination biases in machine learning?
CoRR, 2023
COCKATIEL: COntinuous Concept ranKed ATtribution with Interpretable ELements for explaining neural net classifiers on NLP tasks.
CoRR, 2023
When Mitigating Bias is Unfair: A Comprehensive Study on the Impact of Bias Mitigation Algorithms.
CoRR, 2023
Detecting and Processing Unsuspected Sensitive Variables for Robust Machine Learning.
Algorithms, 2023
Counterfactual Explanation for Multivariate Times Series Using A Contrastive Variational Autoencoder.
Proceedings of the IEEE International Conference on Acoustics, 2023
Is a Fairness Metric Score Enough to Assess Discrimination Biases in Machine Learning?
Proceedings of the 2nd European Workshop on Algorithmic Fairness, 2023
Breaking Bias: How Optimal Transport Can Help to Tackle Gender Biases in NLP Based Job Recommendation Systems?
Proceedings of the 2nd European Workshop on Algorithmic Fairness, 2023
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
COCKATIEL: COntinuous Concept ranKed ATtribution with Interpretable ELements for explaining neural net classifiers on NLP.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023
2022
Nonparametric Bayesian Regression and Classification on Manifolds, With Applications to 3D Cochlear Shapes.
IEEE Trans. Image Process., 2022
Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization.
J. Math. Imaging Vis., 2022
A survey of Identification and mitigation of Machine Learning algorithmic biases in Image Analysis.
CoRR, 2022
Fairness constraint in Structural Econometrics and Application to fair estimation using Instrumental Variables.
CoRR, 2022
2021
Bayesian regression and classification using Gaussian process priors indexed by probability density functions.
Inf. Sci., 2021
Detection of Representative Variables in Complex Systems with Interpretable Rules Using Core-Clusters.
Algorithms, 2021
Achieving Robustness in Classification Using Optimal Transport With Hinge Regularization.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021
2020
IEEE Trans. Big Data, 2020
CoRR, 2020
A survey of bias in Machine Learning through the prism of Statistical Parity for the Adult Data Set.
CoRR, 2020
Minimax optimal goodness-of-fit testing for densities under a local differential privacy constraint.
CoRR, 2020
optimalFlow: optimal transport approach to flow cytometry gating and population matching.
BMC Bioinform., 2020
2019
Central limit theorem and bootstrap procedure for Wasserstein's variations with an application to structural relationships between distributions.
J. Multivar. Anal., 2019
Using Wasserstein-2 regularization to ensure fair decisions with Neural-Network classifiers.
CoRR, 2019
Learning a Gaussian Process Model on the Riemannian Manifold of Non-decreasing Distribution Functions.
Proceedings of the PRICAI 2019: Trends in Artificial Intelligence, 2019
Conditional Anomaly Detection for Quality and Productivity Improvement of Electronics Manufacturing Systems.
Proceedings of the Machine Learning, Optimization, and Data Science, 2019
Proceedings of the 36th International Conference on Machine Learning, 2019
2018
IEEE Trans. Intell. Transp. Syst., 2018
IEEE Trans. Inf. Theory, 2018
Entropic Variable Boosting for Explainability and Interpretability in Machine Learning.
CoRR, 2018
CoRR, 2018
Proceedings of the Machine Learning, Optimization, and Data Science, 2018
2017
2016
IEEE Trans. Intell. Transp. Syst., 2016
2015
A parametric registration model for warped distributions with Wasserstein's distance.
J. Multivar. Anal., 2015
Proceedings of the Geometric Science of Information - Second International Conference, 2015
2014
Oracle Inequalities for a Group Lasso Procedure Applied to Generalized Linear Models in High Dimension.
IEEE Trans. Inf. Theory, 2014
Estimation of covariance functions by a fully data-driven model selection procedure and its application to Kriging spatial interpolation of real rainfall data.
Stat. Methods Appl., 2014
Ingénierie des Systèmes d Inf., 2014
Comput. Stat. Data Anal., 2014
2012
Proceedings of the Mathematical Methods for Signal and Image Analysis and Representation, 2012
2011
Non parametric estimation of the structural expectation of a stochastic increasing function.
Stat. Comput., 2011
J. Mach. Learn. Res., 2011
2009
Statistical M-Estimation and Consistency in Large Deformable Models for Image Warping.
J. Math. Imaging Vis., 2009