Jean-Michel Loubes

88 papers A* 3A 2Misc 1Journal 72Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Evaluating Black-Box Vulnerabilities with Wasserstein-Constrained Data Perturbations. CoRR Adriana Laurindo Monteiro, Jean-Michel Loubes
2026	J	`jnl`	Exact Functional ANOVA Decomposition for Categorical Inputs Models. CoRR Baptiste Ferrere, Nicolas Bousquet, Fabrice Gamboa, Jean-Michel Loubes, Joseph Muré
2026	J	`jnl`	Probing Cultural Signals in Large Language Models through Author Profiling. CoRR Valentin Lafargue, Ariel Guerra-Adames, Emmanuelle Claeys, Elouan Vuichard, Jean-Michel Loubes
2026	J	`jnl`	Token-Efficient Change Detection in LLM APIs. CoRR Timothée Chauvin, Clément Lalanne, Erwan Le Merrer, Jean-Michel Loubes, François Taïani, Gilles Trédan
2025	J	`jnl`	Buzz, Choose, Forget: A Meta-Bandit Framework for Bee-Like Decision Making. CoRR Emmanuelle Claeys, Elena Kerjean, Jean-Michel Loubes
2025	J	`jnl`	Explaining Models under Multivariate Bernoulli Distribution via Hoeffding Decomposition. CoRR Baptiste Ferrere, Nicolas Bousquet, Fabrice Gamboa, Jean-Michel Loubes, Joseph Muré
2025	J	`jnl`	Exposing the Illusion of Fairness: Auditing Vulnerabilities to Distributional Manipulation Attacks. CoRR Valentin Lafargue, Adriana Laurindo Monteiro, Emmanuelle Claeys, Laurent Risser, Jean-Michel Loubes
2025	—	`conf`	Fairness is in the Details : Face Dataset Auditing. ECML/PKDD (10) Valentin Lafargue, Emmanuelle Claeys, Jean-Michel Loubes
2025	A	`conf`	Fairness-Aware Grouping for Continuous Sensitive Variables: Application for Debiasing Face Analysis with Respect to Skin Tone. ECAI Veronika Shilova, Emmanuel Malherbe, Giovanni Palma, Laurent Risser, Jean-Michel Loubes
2025	J	`jnl`	Fairness-Aware Grouping for Continuous Sensitive Variables: Application for Debiasing Face Analysis with respect to Skin Tone. CoRR Veronika Shilova, Emmanuel Malherbe, Giovanni Palma, Laurent Risser, Jean-Michel Loubes
2025	J	`jnl`	Hoeffding decomposition of functions of random dependent variables. J. Multivar. Anal. Marouane Il Idrissi, Nicolas Bousquet, Fabrice Gamboa, Bertrand Iooss, Jean-Michel Loubes
2025	J	`jnl`	Learning with Differentially Private (Sliced) Wasserstein Gradients. CoRR David Rodríguez-Vítores, Clément Lalanne, Jean-Michel Loubes
2025	J	`jnl`	Model-Agnostic Fairness Regularization for GNNs with Incomplete Sensitive Information. CoRR Mahdi Tavassoli Kejani, Fadi Dornaika, Jean-Michel Loubes
2025	A*	`conf`	On the Private Estimation of Smooth Transport Maps. ICML Clément Lalanne, Franck Iutzeler, Jean-Michel Loubes, Julien Chhor
2025	J	`jnl`	PLS-based approach for fair representation learning. CoRR Elena M. De-Diego, Adrián Pérez-Suay, Paula Gordaliza, Jean-Michel Loubes
2025	—	`conf`	When Mitigating Bias is Unfair: Multiplicity and Arbitrariness in Algorithmic Group Fairness. SaTML Natasa Krco, Thibault Laugel, Vincent Grari, Jean-Michel Loubes, Marcin Detyniecki
2025	J	`jnl`	When majority rules, minority loses: bias amplification of gradient descent. CoRR François Bachoc, Jérôme Bolte, Ryan Boustany, Jean-Michel Loubes
2024	J	`jnl`	Debiasing Machine Learning Models by Using Weakly Supervised Learning. CoRR Renan D. B. Brotto, Jean-Michel Loubes, Laurent Risser, Jean-Pierre Florens, Kenji Nose Filho, João M. T. Romano
2024	J	`jnl`	Diversity-Preserving K-Armed Bandits, Revisited. Trans. Mach. Learn. Res. Hédi Hadiji, Sébastien Gerchinovitz, Jean-Michel Loubes, Gilles Stoltz
2024	J	`jnl`	Fair Graph Neural Network with Supervised Contrastive Regularization. CoRR Mahdi Tavassoli Kejani, Fadi Dornaika, Jean-Michel Loubes
2024	J	`jnl`	Fairness seen as global sensitivity analysis. Mach. Learn. Clément Benesse, Fabrice Gamboa, Jean-Michel Loubes, Thibaut Boissin
2024	J	`jnl`	Transport-based Counterfactual Models. J. Mach. Learn. Res. Lucas de Lara, Alberto González-Sanz, Nicholas Asher, Laurent Risser, Jean-Michel Loubes
2023	J	`jnl`	An Improved Central Limit Theorem and Fast Convergence Rates for Entropic Transportation Costs. SIAM J. Math. Data Sci. Eustasio del Barrio, Alberto González-Sanz, Jean-Michel Loubes, Jonathan Niles-Weed
2023	J	`jnl`	Are fairness metric scores enough to assess discrimination biases in machine learning? CoRR Fanny Jourdan, Laurent Risser, Jean-Michel Loubes, Nicholas Asher
2023	J	`jnl`	Attraction-repulsion clustering: a way of promoting diversity linked to demographic parity in fair clustering. Adv. Data Anal. Classif. Eustasio del Barrio, Hristo Inouzhe, Jean-Michel Loubes
2023	—	`conf`	Breaking Bias: How Optimal Transport Can Help to Tackle Gender Biases in NLP Based Job Recommendation Systems? EWAF Fanny Jourdan, Titon Tshiongo Kaninku, Nicholas Asher, Jean-Michel Loubes, Laurent Risser
2023	J	`jnl`	COCKATIEL: COntinuous Concept ranKed ATtribution with Interpretable ELements for explaining neural net classifiers on NLP tasks. CoRR Fanny Jourdan, Agustin Martin Picard, Thomas Fel, Laurent Risser, Jean-Michel Loubes, Nicholas Asher
2023	—	`conf`	COCKATIEL: COntinuous Concept ranKed ATtribution with Interpretable ELements for explaining neural net classifiers on NLP. ACL (Findings) Fanny Jourdan, Agustin Martin Picard, Thomas Fel, Laurent Risser, Jean-Michel Loubes, Nicholas Asher
2023	Misc	`conf`	Counterfactual Explanation for Multivariate Times Series Using A Contrastive Variational Autoencoder. ICASSP William Todo, Merwann Selmani, Béatrice Laurent, Jean-Michel Loubes
2023	J	`jnl`	Detecting and Processing Unsuspected Sensitive Variables for Robust Machine Learning. Algorithms Laurent Risser, Agustin Martin Picard, Lucas Hervier, Jean-Michel Loubes
2023	J	`jnl`	Diffeomorphic Registration Using Sinkhorn Divergences. SIAM J. Imaging Sci. Lucas de Lara, Alberto González-Sanz, Jean-Michel Loubes
2023	J	`jnl`	Fair Kernel Regression through Cross-Covariance Operators. Trans. Mach. Learn. Res. Adrian Perez-Suay, Paula Gordaliza, Jean-Michel Loubes, Dino Sejdinovic, Gustau Camps-Valls
2023	A	`conf`	Gaussian Processes on Distributions based on Regularized Optimal Transport. AISTATS François Bachoc, Louis Béthune, Alberto González-Sanz, Jean-Michel Loubes
2023	J	`jnl`	How Optimal Transport Can Tackle Gender Biases in Multi-Class Neural Network Classifiers for Job Recommendations. Algorithms Fanny Jourdan, Titon Tshiongo Kaninku, Nicholas Asher, Jean-Michel Loubes, Laurent Risser
2023	J	`jnl`	How optimal transport can tackle gender biases in multi-class neural-network classifiers for job recommendations? CoRR Fanny Jourdan, Titon Tshiongo Kaninku, Nicholas Asher, Jean-Michel Loubes, Laurent Risser
2023	—	`conf`	Is a Fairness Metric Score Enough to Assess Discrimination Biases in Machine Learning? EWAF Fanny Jourdan, Ronan Pons, Nicholas Asher, Jean-Michel Loubes, Laurent Risser
2023	J	`jnl`	When Mitigating Bias is Unfair: A Comprehensive Study on the Impact of Bias Mitigation Algorithms. CoRR Natasa Krco, Thibault Laugel, Jean-Michel Loubes, Marcin Detyniecki
2022	J	`jnl`	A survey of Identification and mitigation of Machine Learning algorithmic biases in Image Analysis. CoRR Laurent Risser, Agustin Martin Picard, Lucas Hervier, Jean-Michel Loubes
2022	J	`jnl`	An improved central limit theorem and fast convergence rates for entropic transportation costs. CoRR Eustasio del Barrio, Alberto González-Sanz, Jean-Michel Loubes, Jonathan Niles-Weed
2022	J	`jnl`	Dimension Reduction for time series with Variational AutoEncoders. CoRR William Todo, Béatrice Laurent, Jean-Michel Loubes, Merwann Selmani
2022	J	`jnl`	Fairness constraint in Structural Econometrics and Application to fair estimation using Instrumental Variables. CoRR Samuele Centorrino, Jean-Pierre Florens, Jean-Michel Loubes
2022	J	`jnl`	GAN Estimation of Lipschitz Optimal Transport Maps. CoRR Alberto González-Sanz, Lucas de Lara, Louis Béthune, Jean-Michel Loubes
2022	J	`jnl`	Gaussian Processes on Distributions based on Regularized Optimal Transport. CoRR François Bachoc, Louis Béthune, Alberto González-Sanz, Jean-Michel Loubes
2022	J	`jnl`	Nonparametric Bayesian Regression and Classification on Manifolds, With Applications to 3D Cochlear Shapes. IEEE Trans. Image Process. Anis Fradi, Chafik Samir, José Braga, Shantanu H. Joshi, Jean-Michel Loubes
2022	J	`jnl`	Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization. J. Math. Imaging Vis. Laurent Risser, Alberto González-Sanz, Quentin Vincenot, Jean-Michel Loubes
2021	A*	`conf`	Achieving Robustness in Classification Using Optimal Transport With Hinge Regularization. CVPR Mathieu Serrurier, Franck Mamalet, Alberto González-Sanz, Thibaut Boissin, Jean-Michel Loubes, Eustasio del Barrio
2021	J	`jnl`	Bayesian regression and classification using Gaussian process priors indexed by probability density functions. Inf. Sci. Anis Fradi, Yan Feunteun, Chafik Samir, M. Baklouti, François Bachoc, Jean-Michel Loubes
2021	J	`jnl`	Detection of Representative Variables in Complex Systems with Interpretable Rules Using Core-Clusters. Algorithms Camille Champion, Anne-Claire Brunet, Rémy Burcelin, Jean-Michel Loubes, Laurent Risser
2021	J	`jnl`	Transport-based Counterfactual Models. CoRR Lucas de Lara, Alberto González-Sanz, Nicholas Asher, Jean-Michel Loubes
2020	J	`jnl`	A survey of bias in Machine Learning through the prism of Statistical Parity for the Adult Data Set. CoRR Philippe C. Besse, Eustasio del Barrio, Paula Gordaliza, Jean-Michel Loubes, Laurent Risser
2020	J	`jnl`	Achieving robustness in classification using optimal transport with hinge regularization. CoRR Mathieu Serrurier, Franck Mamalet, Alberto González-Sanz, Thibaut Boissin, Jean-Michel Loubes, Eustasio del Barrio
2020	J	`jnl`	Diversity-Preserving K-Armed Bandits, Revisited. CoRR Hédi Hadiji, Sébastien Gerchinovitz, Jean-Michel Loubes, Gilles Stoltz
2020	J	`jnl`	Minimax optimal goodness-of-fit testing for densities under a local differential privacy constraint. CoRR Joseph Lam-Weil, Béatrice Laurent, Jean-Michel Loubes
2020	J	`jnl`	Multiple Testing for Outlier Detection in Space Telemetries. IEEE Trans. Big Data Clémentine Barreyre, Béatrice Laurent, Jean-Michel Loubes, Loïc Boussouf, Bertrand Cabon
2020	J	`jnl`	Review of Mathematical frameworks for Fairness in Machine Learning. CoRR Eustasio del Barrio, Paula Gordaliza, Jean-Michel Loubes
2020	J	`jnl`	Robust spectral clustering using LASSO regularization. CoRR Camille Champion, Mélanie Blazère, Rémy Burcelin, Jean-Michel Loubes, Laurent Risser
2020	J	`jnl`	The price for fairness in a regression framework. CoRR Thibaut Le Gouic, Jean-Michel Loubes
2020	J	`jnl`	The statistical effect of entropic regularization in optimal transportation. CoRR Eustasio del Barrio, Jean-Michel Loubes
2020	J	`jnl`	optimalFlow: optimal transport approach to flow cytometry gating and population matching. BMC Bioinform. Eustasio del Barrio, Hristo Inouzhe, Jean-Michel Loubes, Carlos Matrán, Agustín Mayo-Íscar
2019	J	`jnl`	Attraction-Repulsion clustering with applications to fairness. CoRR Eustasio del Barrio, Hristo Inouzhe, Jean-Michel Loubes
2019	J	`jnl`	Central limit theorem and bootstrap procedure for Wasserstein's variations with an application to structural relationships between distributions. J. Multivar. Anal. Eustasio del Barrio, Paula Gordaliza, Hélène Lescornel, Jean-Michel Loubes
2019	—	`conf`	Conditional Anomaly Detection for Quality and Productivity Improvement of Electronics Manufacturing Systems. LOD Eva Jabbar, Philippe C. Besse, Jean-Michel Loubes, Christophe Merle
2019	—	`conf`	Learning a Gaussian Process Model on the Riemannian Manifold of Non-decreasing Distribution Functions. PRICAI (2) Chafik Samir, Jean-Michel Loubes, Anne-Françoise Yao, François Bachoc
2019	A*	`conf`	Obtaining Fairness using Optimal Transport Theory. ICML Paula Gordaliza, Eustasio del Barrio, Fabrice Gamboa, Jean-Michel Loubes
2019	J	`jnl`	Using Wasserstein-2 regularization to ensure fair decisions with Neural-Network classifiers. CoRR Laurent Risser, Quentin Vincenot, Nicolas P. Couellan, Jean-Michel Loubes
2019	J	`jnl`	optimalFlow: Optimal-transport approach to flow cytometry gating and population matching. CoRR Eustasio del Barrio, Hristo Inouzhe, Jean-Michel Loubes, Carlos Matrán, Agustín Mayo-Íscar
2018	J	`jnl`	A Gaussian Process Regression Model for Distribution Inputs. IEEE Trans. Inf. Theory François Bachoc, Fabrice Gamboa, Jean-Michel Loubes, Nil Venet
2018	J	`jnl`	COREclust: a new package for a robust and scalable analysis of complex data. CoRR Camille Champion, Anne-Claire Brunet, Jean-Michel Loubes, Laurent Risser
2018	J	`jnl`	Can everyday AI be ethical. Fairness of Machine Learning Algorithms. CoRR Philippe C. Besse, Céline Castets-Renard, Aurélien Garivier, Jean-Michel Loubes
2018	J	`jnl`	Confidence Intervals for Testing Disparate Impact in Fair Learning. CoRR Philippe C. Besse, Eustasio del Barrio, Paula Gordaliza, Jean-Michel Loubes
2018	J	`jnl`	Destination Prediction by Trajectory Distribution-Based Model. IEEE Trans. Intell. Transp. Syst. Philippe C. Besse, Brendan Guillouet, Jean-Michel Loubes, Francois Royer
2018	J	`jnl`	Entropic Variable Boosting for Explainability and Interpretability in Machine Learning. CoRR François Bachoc, Fabrice Gamboa, Jean-Michel Loubes, Laurent Risser
2018	—	`conf`	Supervised Learning Approach for Surface-Mount Device Production. LOD Eva Jabbar, Philippe C. Besse, Jean-Michel Loubes, Nathalie Barbosa Roa, Christophe Merle, Rémi Dettai
2017	J	`jnl`	Deep Learning applied to Road Traffic Speed forecasting. CoRR Thomas Epelbaum, Fabrice Gamboa, Jean-Michel Loubes, Jessica Martin
2016	J	`jnl`	Big Data analytics. Three use cases with R, Python and Spark. CoRR Philippe C. Besse, Brendan Guillouet, Jean-Michel Loubes
2016	J	`jnl`	Review and Perspective for Distance-Based Clustering of Vehicle Trajectories. IEEE Trans. Intell. Transp. Syst. Philippe C. Besse, Brendan Guillouet, Jean-Michel Loubes, Francois Royer
2015	J	`jnl`	A parametric registration model for warped distributions with Wasserstein's distance. J. Multivar. Anal. Marina Agulló-Antolín, Juan Antonio Cuesta-Albertos, Hélène Lescornel, Jean-Michel Loubes
2015	—	`conf`	Barycenter in Wasserstein Spaces: Existence and Consistency. GSI Thibaut Le Gouic, Jean-Michel Loubes
2015	J	`jnl`	Review and Perspective for Distance Based Trajectory Clustering. CoRR Philippe C. Besse, Brendan Guillouet, Jean-Michel Loubes, François Royer
2014	J	`jnl`	A robust algorithm for template curve estimation based on manifold embedding. Comput. Stat. Data Anal. Chloé Dimeglio, Santiago Gallón, Jean-Michel Loubes, Elie Maza
2014	J	`jnl`	Big Data - Retour vers le Futur 3; De Statisticien à Data Scientist. CoRR Philippe C. Besse, Aurélien Garivier, Jean-Michel Loubes
2014	J	`jnl`	Big data analytics - Retour vers le futur 3. De statisticien à data scientist. Ingénierie des Systèmes d Inf. Philippe C. Besse, Aurélien Garivier, Jean-Michel Loubes
2014	J	`jnl`	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. Rolando Biscay Lirio, Dunia Giniebra Camejo, Jean-Michel Loubes, Lilian Muñiz-Alvarez
2014	J	`jnl`	Oracle Inequalities for a Group Lasso Procedure Applied to Generalized Linear Models in High Dimension. IEEE Trans. Inf. Theory Mélanie Blazère, Jean-Michel Loubes, Fabrice Gamboa
2012	—	`ch.`	Regularization with Approximated L 2 Maximum Entropy Method. Mathematical Methods for Signal and Image Analysis and Representation Jean-Michel Loubes, Paul Rochet
2011	J	`jnl`	Group Lasso Estimation of High-dimensional Covariance Matrices. J. Mach. Learn. Res. Jérémie Bigot, Rolando J. Biscay, Jean-Michel Loubes, Lilian Muñiz-Alvarez
2011	J	`jnl`	Non parametric estimation of the structural expectation of a stochastic increasing function. Stat. Comput. Jean-François Dupuy, Jean-Michel Loubes, Elie Maza
2009	J	`jnl`	Statistical M-Estimation and Consistency in Large Deformable Models for Image Warping. J. Math. Imaging Vis. Jérémie Bigot, Sébastien Gadat, Jean-Michel Loubes