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ORCIDJean-Michel Loubes
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2020 – today
- 2024
[j27]Lucas de Lara, Alberto González-Sanz, Nicholas Asher, Laurent Risser, Jean-Michel Loubes:
Transport-based Counterfactual Models. J. Mach. Learn. Res. 25: 136:1-136:59 (2024)- [j26]Clément Benesse
, Fabrice Gamboa, Jean-Michel Loubes, Thibaut Boissin:
Fairness seen as global sensitivity analysis. Mach. Learn. 113(5): 3205-3232 (2024) - [j25]Hédi Hadiji, Sébastien Gerchinovitz, Jean-Michel Loubes, Gilles Stoltz:
Diversity-Preserving K-Armed Bandits, Revisited. Trans. Mach. Learn. Res. 2024 (2024) - [i32]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 abs/2402.15477 (2024) - [i31]Mahdi Tavassoli Kejani, Fadi Dornaika, Jean-Michel Loubes:
Fair Graph Neural Network with Supervised Contrastive Regularization. CoRR abs/2404.06090 (2024) - 2023
- [j24]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): 859-896 (2023) - [j23]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): 174 (2023) - [j22]Laurent Risser, Agustin Martin Picard, Lucas Hervier, Jean-Michel Loubes:
Detecting and Processing Unsuspected Sensitive Variables for Robust Machine Learning. Algorithms 16(11): 510 (2023) - [j21]Lucas de Lara, Alberto González-Sanz, Jean-Michel Loubes:
Diffeomorphic Registration Using Sinkhorn Divergences. SIAM J. Imaging Sci. 16(1): 250-279 (2023) - [j20]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): 639-669 (2023) - [j19]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) - [c11]Fanny Jourdan, Agustin Martin 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: 5120-5136 - [c10]François Bachoc, Louis Béthune, Alberto González-Sanz, Jean-Michel Loubes:
Gaussian Processes on Distributions based on Regularized Optimal Transport. AISTATS 2023: 4986-5010 - [c9]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 - [c8]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 - [c7]William Todo, Merwann Selmani, Béatrice Laurent, Jean-Michel Loubes:
Counterfactual Explanation for Multivariate Times Series Using A Contrastive Variational Autoencoder. ICASSP 2023: 1-5 - [i30]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 abs/2302.07185 (2023) - [i29]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 abs/2302.14063 (2023) - [i28]Fanny Jourdan, Agustin Martin 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 abs/2305.06754 (2023) - [i27]Fanny Jourdan, Laurent Risser, Jean-Michel Loubes, Nicholas Asher:
Are fairness metric scores enough to assess discrimination biases in machine learning? CoRR abs/2306.05307 (2023) - 2022
- [j18]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): 672-689 (2022) - [j17]Anis Fradi, Chafik Samir, José 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: 2598-2607 (2022) - [i26]Alberto González-Sanz, Lucas de Lara, Louis Béthune, Jean-Michel Loubes:
GAN Estimation of Lipschitz Optimal Transport Maps. CoRR abs/2202.07965 (2022) - [i25]Samuele Centorrino, Jean-Pierre Florens, Jean-Michel Loubes:
Fairness constraint in Structural Econometrics and Application to fair estimation using Instrumental Variables. CoRR abs/2202.08977 (2022) - [i24]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 abs/2204.09105 (2022) - [i23]William Todo, Béatrice Laurent, Jean-Michel Loubes, Merwann Selmani:
Dimension Reduction for time series with Variational AutoEncoders. CoRR abs/2204.11060 (2022) - [i22]Laurent Risser, Agustin Martin Picard, Lucas Hervier, Jean-Michel Loubes:
A survey of Identification and mitigation of Machine Learning algorithmic biases in Image Analysis. CoRR abs/2210.04491 (2022) - [i21]François Bachoc, Louis Béthune, Alberto González-Sanz, Jean-Michel Loubes:
Gaussian Processes on Distributions based on Regularized Optimal Transport. CoRR abs/2210.06574 (2022) - 2021
- [j16]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): 66 (2021) - [j15]Anis Fradi, Yan 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: 56-68 (2021) - [c6]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: 505-514 - [i20]Lucas de Lara, Alberto González-Sanz, Nicholas Asher, Jean-Michel Loubes:
Transport-based Counterfactual Models. CoRR abs/2108.13025 (2021) - 2020
- [j14]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): 479 (2020) - [j13]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): 443-451 (2020) - [i19]Joseph Lam-Weil, Béatrice Laurent, Jean-Michel Loubes:
Minimax optimal goodness-of-fit testing for densities under a local differential privacy constraint. CoRR abs/2002.04254 (2020) - [i18]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 abs/2003.14263 (2020) - [i17]Camille Champion, Mélanie Blazère, Rémy Burcelin, Jean-Michel Loubes, Laurent Risser:
Robust spectral clustering using LASSO regularization. CoRR abs/2004.03845 (2020) - [i16]Thibaut Le Gouic, Jean-Michel Loubes:
The price for fairness in a regression framework. CoRR abs/2005.11720 (2020) - [i15]Eustasio del Barrio, Paula Gordaliza, Jean-Michel Loubes:
Review of Mathematical frameworks for Fairness in Machine Learning. CoRR abs/2005.13755 (2020) - [i14]Eustasio del Barrio, Jean-Michel Loubes:
The statistical effect of entropic regularization in optimal transportation. CoRR abs/2006.05199 (2020) - [i13]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 abs/2006.06520 (2020) - [i12]Hédi Hadiji, Sébastien Gerchinovitz, Jean-Michel Loubes, Gilles Stoltz:
Diversity-Preserving K-Armed Bandits, Revisited. CoRR abs/2010.01874 (2020)
2010 – 2019
- 2019
- [j12]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: 341-362 (2019) - [c5]Paula Gordaliza, Eustasio del Barrio, Fabrice Gamboa, Jean-Michel Loubes:
Obtaining Fairness using Optimal Transport Theory. ICML 2019: 2357-2365 - [c4]Eva Jabbar, Philippe C. Besse, Jean-Michel Loubes, Christophe Merle:
Conditional Anomaly Detection for Quality and Productivity Improvement of Electronics Manufacturing Systems. LOD 2019: 711-724 - [c3]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: 107-120 - [i11]Eustasio del Barrio, Hristo Inouzhe, Jean-Michel Loubes:
Attraction-Repulsion clustering with applications to fairness. CoRR abs/1904.05254 (2019) - [i10]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 abs/1907.08006 (2019) - [i9]Laurent Risser, Quentin Vincenot, Nicolas P. Couellan, Jean-Michel Loubes:
Using Wasserstein-2 regularization to ensure fair decisions with Neural-Network classifiers. CoRR abs/1908.05783 (2019) - 2018
- [j11]François Bachoc, Fabrice Gamboa, Jean-Michel Loubes, Nil Venet:
A Gaussian Process Regression Model for Distribution Inputs. IEEE Trans. Inf. Theory 64(10): 6620-6637 (2018) - [j10]Philippe C. Besse, Brendan Guillouet, Jean-Michel Loubes, Francois Royer:
Destination Prediction by Trajectory Distribution-Based Model. IEEE Trans. Intell. Transp. Syst. 19(8): 2470-2481 (2018) - [c2]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: 254-263 - [i8]Camille Champion, Anne-Claire Brunet, Jean-Michel Loubes, Laurent Risser:
COREclust: a new package for a robust and scalable analysis of complex data. CoRR abs/1805.10211 (2018) - [i7]Philippe C. Besse, Eustasio del Barrio, Paula Gordaliza, Jean-Michel Loubes:
Confidence Intervals for Testing Disparate Impact in Fair Learning. CoRR abs/1807.06362 (2018) - [i6]Philippe C. Besse, Céline Castets-Renard, Aurélien Garivier, Jean-Michel Loubes:
Can everyday AI be ethical. Fairness of Machine Learning Algorithms. CoRR abs/1810.01729 (2018) - [i5]François Bachoc, Fabrice Gamboa, Jean-Michel Loubes, Laurent Risser:
Entropic Variable Boosting for Explainability and Interpretability in Machine Learning. CoRR abs/1810.07924 (2018) - 2017
- [i4]Thomas Epelbaum, Fabrice Gamboa, Jean-Michel Loubes, Jessica Martin:
Deep Learning applied to Road Traffic Speed forecasting. CoRR abs/1710.08266 (2017) - 2016
- [j9]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): 3306-3317 (2016) - [i3]Philippe C. Besse, Brendan Guillouet, Jean-Michel Loubes:
Big Data analytics. Three use cases with R, Python and Spark. CoRR abs/1609.09619 (2016) - 2015
- [j8]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: 117-130 (2015) - [c1]Thibaut Le Gouic, Jean-Michel Loubes:
Barycenter in Wasserstein Spaces: Existence and Consistency. GSI 2015: 104-108 - [i2]Philippe C. Besse, Brendan Guillouet, Jean-Michel Loubes, François Royer:
Review and Perspective for Distance Based Trajectory Clustering. CoRR abs/1508.04904 (2015) - 2014
- [j7]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: 373-386 (2014) - [j6]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): 93-105 (2014) - [j5]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): 149-174 (2014) - [j4]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): 2303-2318 (2014) - [i1]Philippe C. Besse, Aurélien Garivier, Jean-Michel Loubes:
Big Data - Retour vers le Futur 3; De Statisticien à Data Scientist. CoRR abs/1403.3758 (2014) - 2012
- [p1]Jean-Michel Loubes, Paul Rochet:
Regularization with Approximated L 2 Maximum Entropy Method. Mathematical Methods for Signal and Image Analysis and Representation 2012: 275-290 - 2011
- [j3]Jérémie Bigot, Rolando J. Biscay, Jean-Michel Loubes, Lilian Muñiz-Alvarez:
Group Lasso Estimation of High-dimensional Covariance Matrices. J. Mach. Learn. Res. 12: 3187-3225 (2011) - [j2]Jean-François Dupuy, Jean-Michel Loubes, Elie Maza:
Non parametric estimation of the structural expectation of a stochastic increasing function. Stat. Comput. 21(1): 121-136 (2011)
2000 – 2009
- 2009
- [j1]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): 270-290 (2009)
Coauthor Index
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last updated on 2024-10-07 21:15 CEST by the dblp team
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