Jean-Michel Loubes

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 58

Top Topics

Central Limit Theorem

Gaussian Process

Machine Learning

Big Data Analytics

Top Venues

IEEE Trans. Inf. Theory

Publications

Hédi Hadiji, Sébastien Gerchinovitz, Jean-Michel Loubes, Gilles Stoltz
Diversity-Preserving K-Armed Bandits, Revisited. Trans. Mach. Learn. Res. 2024 (2024)
Mahdi Tavassoli Kejani, Fadi Dornaika, Jean-Michel Loubes
Fair Graph Neural Network with Supervised Contrastive Regularization. CoRR (2024)
Clément Benesse, Fabrice Gamboa, Jean-Michel Loubes, Thibaut Boissin
Fairness seen as global sensitivity analysis. Mach. Learn. 113 (5) (2024)
Renan D. B. Brotto, Jean-Michel Loubes, Laurent Risser, Jean-Pierre Florens, Kenji Nose Filho, João M. T. Romano
Debiasing Machine Learning Models by Using Weakly Supervised Learning. CoRR (2024)
Fanny Jourdan, Titon Tshiongo Kaninku, Nicholas Asher, Jean-Michel Loubes, Laurent Risser
How Optimal Transport Can Tackle Gender Biases in Multi-Class Neural Network Classifiers for Job Recommendations. Algorithms 16 (3) (2023)
Eustasio del Barrio, Hristo Inouzhe, Jean-Michel Loubes
Attraction-repulsion clustering: a way of promoting diversity linked to demographic parity in fair clustering. Adv. Data Anal. Classif. 17 (4) (2023)
Lucas de Lara, Alberto González-Sanz, Jean-Michel Loubes
Diffeomorphic Registration Using Sinkhorn Divergences. SIAM J. Imaging Sci. 16 (1) (2023)
François Bachoc, Louis Béthune, Alberto González-Sanz, Jean-Michel Loubes
Gaussian Processes on Distributions based on Regularized Optimal Transport. AISTATS (2023)
Eustasio del Barrio, Alberto González-Sanz, Jean-Michel Loubes, Jonathan Niles-Weed
An Improved Central Limit Theorem and Fast Convergence Rates for Entropic Transportation Costs. SIAM J. Math. Data Sci. 5 (3) (2023)
Fanny Jourdan, Laurent Risser, Jean-Michel Loubes, Nicholas Asher
Are fairness metric scores enough to assess discrimination biases in machine learning? CoRR (2023)
Natasa Krco, Thibault Laugel, Jean-Michel Loubes, Marcin Detyniecki
When Mitigating Bias is Unfair: A Comprehensive Study on the Impact of Bias Mitigation Algorithms. CoRR (2023)
Fanny Jourdan, Agustin Picard, Thomas Fel, Laurent Risser, Jean-Michel Loubes, Nicholas Asher
COCKATIEL: COntinuous Concept ranKed ATtribution with Interpretable ELements for explaining neural net classifiers on NLP. ACL (Findings) (2023)
Adrian Perez-Suay, Paula Gordaliza, Jean-Michel Loubes, Dino Sejdinovic, Gustau Camps-Valls
Fair Kernel Regression through Cross-Covariance Operators. Trans. Mach. Learn. Res. 2023 (2023)
Laurent Risser, Agustin Martin Picard, Lucas Hervier, Jean-Michel Loubes
Detecting and Processing Unsuspected Sensitive Variables for Robust Machine Learning. Algorithms 16 (11) (2023)
William Todo, Merwann Selmani, Béatrice Laurent, Jean-Michel Loubes
Counterfactual Explanation for Multivariate Times Series Using A Contrastive Variational Autoencoder. ICASSP (2023)
Fanny Jourdan, Agustin Picard, Thomas Fel, Laurent Risser, Jean-Michel Loubes, Nicholas Asher
COCKATIEL: COntinuous Concept ranKed ATtribution with Interpretable ELements for explaining neural net classifiers on NLP tasks. CoRR (2023)
Fanny Jourdan, Ronan Pons, Nicholas Asher, Jean-Michel Loubes, Laurent Risser
Is a Fairness Metric Score Enough to Assess Discrimination Biases in Machine Learning? EWAF (2023)
Fanny Jourdan, Titon Tshiongo Kaninku, Nicholas Asher, Jean-Michel Loubes, Laurent Risser
How optimal transport can tackle gender biases in multi-class neural-network classifiers for job recommendations? CoRR (2023)
Fanny Jourdan, Titon Tshiongo Kaninku, Nicholas Asher, Jean-Michel Loubes, Laurent Risser
Breaking Bias: How Optimal Transport Can Help to Tackle Gender Biases in NLP Based Job Recommendation Systems? EWAF (2023)
William Todo, Béatrice Laurent, Jean-Michel Loubes, Merwann Selmani
Dimension Reduction for time series with Variational AutoEncoders. CoRR (2022)
Anis Fradi, Chafik Samir, J. Braga, Shantanu H. Joshi, Jean-Michel Loubes
Nonparametric Bayesian Regression and Classification on Manifolds, With Applications to 3D Cochlear Shapes. IEEE Trans. Image Process. 31 (2022)
Laurent Risser, Agustin Picard, Lucas Hervier, Jean-Michel Loubes
A survey of Identification and mitigation of Machine Learning algorithmic biases in Image Analysis. CoRR (2022)
Eustasio del Barrio, Alberto González-Sanz, Jean-Michel Loubes, Jonathan Niles-Weed
An improved central limit theorem and fast convergence rates for entropic transportation costs. CoRR (2022)
François Bachoc, Louis Béthune, Alberto González-Sanz, Jean-Michel Loubes
Gaussian Processes on Distributions based on Regularized Optimal Transport. CoRR (2022)
Samuele Centorrino, Jean-Pierre Florens, Jean-Michel Loubes
Fairness constraint in Structural Econometrics and Application to fair estimation using Instrumental Variables. CoRR (2022)
Laurent Risser, Alberto González-Sanz, Quentin Vincenot, Jean-Michel Loubes
Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization. J. Math. Imaging Vis. 64 (6) (2022)
Alberto González-Sanz, Lucas de Lara, Louis Béthune, Jean-Michel Loubes
GAN Estimation of Lipschitz Optimal Transport Maps. CoRR (2022)
Anis Fradi, Y. Feunteun, Chafik Samir, M. Baklouti, François Bachoc, Jean-Michel Loubes
Bayesian regression and classification using Gaussian process priors indexed by probability density functions. Inf. Sci. 548 (2021)
Lucas de Lara, Alberto González-Sanz, Nicholas Asher, Jean-Michel Loubes
Transport-based Counterfactual Models. CoRR (2021)
Mathieu Serrurier, Franck Mamalet, Alberto González-Sanz, Thibaut Boissin, Jean-Michel Loubes, Eustasio del Barrio
Achieving Robustness in Classification Using Optimal Transport With Hinge Regularization. CVPR (2021)
Camille Champion, Anne-Claire Brunet, Rémy Burcelin, Jean-Michel Loubes, Laurent Risser
Detection of Representative Variables in Complex Systems with Interpretable Rules Using Core-Clusters. Algorithms 14 (2) (2021)
Joseph Lam-Weil, Béatrice Laurent, Jean-Michel Loubes
Minimax optimal goodness-of-fit testing for densities under a local differential privacy constraint. CoRR (2020)
Mathieu Serrurier, Franck Mamalet, Alberto González-Sanz, Thibaut Boissin, Jean-Michel Loubes, Eustasio del Barrio
Achieving robustness in classification using optimal transport with hinge regularization. CoRR (2020)
Clémentine Barreyre, Béatrice Laurent, Jean-Michel Loubes, Loïc Boussouf, Bertrand Cabon
Multiple Testing for Outlier Detection in Space Telemetries. IEEE Trans. Big Data 6 (3) (2020)
Hédi Hadiji, Sébastien Gerchinovitz, Jean-Michel Loubes, Gilles Stoltz
Diversity-Preserving K-Armed Bandits, Revisited. CoRR (2020)
Eustasio del Barrio, Hristo Inouzhe, Jean-Michel Loubes, Carlos Matrán, Agustín Mayo-Íscar
optimalFlow: optimal transport approach to flow cytometry gating and population matching. BMC Bioinform. 21 (1) (2020)
Eustasio del Barrio, Paula Gordaliza, Jean-Michel Loubes
Review of Mathematical frameworks for Fairness in Machine Learning. CoRR (2020)
Philippe C. Besse, Eustasio del Barrio, Paula Gordaliza, Jean-Michel Loubes, Laurent Risser
A survey of bias in Machine Learning through the prism of Statistical Parity for the Adult Data Set. CoRR (2020)
Thibaut Le Gouic, Jean-Michel Loubes
The price for fairness in a regression framework. CoRR (2020)
Camille Champion, Mélanie Blazère, Rémy Burcelin, Jean-Michel Loubes, Laurent Risser
Robust spectral clustering using LASSO regularization. CoRR (2020)
Eustasio del Barrio, Jean-Michel Loubes
The statistical effect of entropic regularization in optimal transportation. CoRR (2020)
Eva Jabbar, Philippe C. Besse, Jean-Michel Loubes, Christophe Merle
Conditional Anomaly Detection for Quality and Productivity Improvement of Electronics Manufacturing Systems. LOD (2019)
Eustasio del Barrio, Paula Gordaliza, Hélène Lescornel, Jean-Michel Loubes
Central limit theorem and bootstrap procedure for Wasserstein's variations with an application to structural relationships between distributions. J. Multivar. Anal. 169 (2019)
Chafik Samir, Jean-Michel Loubes, Anne-Françoise Yao, François Bachoc
Learning a Gaussian Process Model on the Riemannian Manifold of Non-decreasing Distribution Functions. PRICAI (2) (2019)
Paula Gordaliza, Eustasio del Barrio, Fabrice Gamboa, Jean-Michel Loubes
Obtaining Fairness using Optimal Transport Theory. ICML (2019)
Eustasio del Barrio, Hristo Inouzhe, Jean-Michel Loubes
Attraction-Repulsion clustering with applications to fairness. CoRR (2019)
Eustasio del Barrio, Hristo Inouzhe, Jean-Michel Loubes, Carlos Matrán, Agustín Mayo-Íscar
optimalFlow: Optimal-transport approach to flow cytometry gating and population matching. CoRR (2019)
Laurent Risser, Quentin Vincenot, Nicolas P. Couellan, Jean-Michel Loubes
Using Wasserstein-2 regularization to ensure fair decisions with Neural-Network classifiers. CoRR (2019)
Philippe C. Besse, Brendan Guillouet, Jean-Michel Loubes, Francois Royer
Destination Prediction by Trajectory Distribution-Based Model. IEEE Trans. Intell. Transp. Syst. 19 (8) (2018)
Philippe C. Besse, Eustasio del Barrio, Paula Gordaliza, Jean-Michel Loubes
Confidence Intervals for Testing Disparate Impact in Fair Learning. CoRR (2018)
François Bachoc, Fabrice Gamboa, Jean-Michel Loubes, Nil Venet
A Gaussian Process Regression Model for Distribution Inputs. IEEE Trans. Inf. Theory 64 (10) (2018)
Camille Champion, Anne-Claire Brunet, Jean-Michel Loubes, Laurent Risser
COREclust: a new package for a robust and scalable analysis of complex data. CoRR (2018)
Philippe C. Besse, Céline Castets-Renard, Aurélien Garivier, Jean-Michel Loubes
Can everyday AI be ethical. Fairness of Machine Learning Algorithms. CoRR (2018)
Eva Jabbar, Philippe C. Besse, Jean-Michel Loubes, Nathalie Barbosa Roa, Christophe Merle, Rémi Dettai
Supervised Learning Approach for Surface-Mount Device Production. LOD (2018)
François Bachoc, Fabrice Gamboa, Jean-Michel Loubes, Laurent Risser
Entropic Variable Boosting for Explainability and Interpretability in Machine Learning. CoRR (2018)
Thomas Epelbaum, Fabrice Gamboa, Jean-Michel Loubes, Jessica Martin
Deep Learning applied to Road Traffic Speed forecasting. CoRR (2017)
Philippe C. Besse, Brendan Guillouet, Jean-Michel Loubes
Big Data analytics. Three use cases with R, Python and Spark. CoRR (2016)
Philippe C. Besse, Brendan Guillouet, Jean-Michel Loubes, Francois Royer
Review and Perspective for Distance-Based Clustering of Vehicle Trajectories. IEEE Trans. Intell. Transp. Syst. 17 (11) (2016)
Marina Agulló-Antolín, Juan Antonio Cuesta-Albertos, Hélène Lescornel, Jean-Michel Loubes
A parametric registration model for warped distributions with Wasserstein's distance. J. Multivar. Anal. 135 (2015)
Philippe C. Besse, Brendan Guillouet, Jean-Michel Loubes, François Royer
Review and Perspective for Distance Based Trajectory Clustering. CoRR (2015)
Thibaut Le Gouic, Jean-Michel Loubes
Barycenter in Wasserstein Spaces: Existence and Consistency. GSI (2015)
Philippe C. Besse, Aurélien Garivier, Jean-Michel Loubes
Big data analytics - Retour vers le futur 3. De statisticien à data scientist. Ingénierie des Systèmes d Inf. 19 (3) (2014)
Philippe C. Besse, Aurélien Garivier, Jean-Michel Loubes
Big Data - Retour vers le Futur 3; De Statisticien à Data Scientist. CoRR (2014)
Chloé Dimeglio, Santiago Gallón, Jean-Michel Loubes, Elie Maza
A robust algorithm for template curve estimation based on manifold embedding. Comput. Stat. Data Anal. 70 (2014)
Rolando Biscay Lirio, Dunia Giniebra Camejo, Jean-Michel Loubes, Lilian Muñiz-Alvarez
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. 23 (2) (2014)
Mélanie Blazère, Jean-Michel Loubes, Fabrice Gamboa
Oracle Inequalities for a Group Lasso Procedure Applied to Generalized Linear Models in High Dimension. IEEE Trans. Inf. Theory 60 (4) (2014)
Jean-François Dupuy, Jean-Michel Loubes, Elie Maza
Non parametric estimation of the structural expectation of a stochastic increasing function. Stat. Comput. 21 (1) (2011)
Jérémie Bigot, Rolando J. Biscay, Jean-Michel Loubes, Lilian Muñiz-Alvarez
Group Lasso Estimation of High-dimensional Covariance Matrices. J. Mach. Learn. Res. 12 (2011)
Jérémie Bigot, Sébastien Gadat, Jean-Michel Loubes
Statistical M-Estimation and Consistency in Large Deformable Models for Image Warping. J. Math. Imaging Vis. 34 (3) (2009)