Marc Sebban - RankMe

131 papers A* 15A 2B 17Misc 6Journal 49Unranked 40

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	A Bregman Proximal Viewpoint on Neural Operators. ICML Abdel-Rahim Mezidi, Jordan Patracone, Saverio Salzo, Amaury Habrard, Massimiliano Pontil, Rémi Emonet, Marc Sebban
2025	J	`jnl`	Méthode de quadrature pour les PINNs fondée théoriquement sur la hessienne des résiduels. CoRR Antoine Caradot, Rémi Emonet, Amaury Habrard, Abdel-Rahim Mezidi, Marc Sebban
2025	B	`conf`	Physics-Informed Machine Learning for Modeling CO2 Capture from Scarce Data. ICTAI Mickael Gault, Pierre Bachaud, Benoît Celse, Rémi Emonet, Marc Sebban
2025	—	`conf`	Provably Accurate Adaptive Sampling for Collocation Points in Physics-Informed Neural Networks. ECML/PKDD (5) Antoine Caradot, Rémi Emonet, Amaury Habrard, Abdel-Rahim Mezidi, Marc Sebban
2025	J	`jnl`	Provably accurate adaptive sampling for collocation points in physics-informed neural networks. CoRR Antoine Caradot, Rémi Emonet, Amaury Habrard, Abdel-Rahim Mezidi, Marc Sebban
2025	J	`jnl`	Unrolled-SINDy: A Stable Explicit Method for Non linear PDE Discovery from Sparsely Sampled Data. CoRR Fayad Ali Banna, Antoine Caradot, Eduardo Brandao, Jean-Philippe Colombier, Rémi Emonet, Marc Sebban
2024	—	`conf`	Approximation Error of Sobolev Regular Functions with Tanh Neural Networks: Theoretical Impact on PINNs. ECML/PKDD (4) Benjamin Girault, Rémi Emonet, Amaury Habrard, Jordan Patracone, Marc Sebban
2024	B	`conf`	Generative shape deformation with optimal transport using learned transformations. IJCNN Jorge Azorín López, Marc Sebban, Nahuel E. Garcia-D'Urso, Amaury Habrard, Andrés Fuster Guilló
2024	B	`conf`	Physics-Informed Machine Learning for Better Understanding Laser-Matter Interaction. ICTAI Fayad Ali Banna, Jean-Philippe Colombier, Rémi Emonet, Marc Sebban
2024	B	`conf`	Unsupervised Learning and Effective Complexity: Introducing JPG and Neural Sophistication. ICTAI Erick Gomez Soto, Rémi Emonet, Marc Sebban
2023	—	`conf`	Is My Neural Net Driven by the MDL Principle? ECML/PKDD (2) Eduardo Brandao, Stefan Duffner, Rémi Emonet, Amaury Habrard, François Jacquenet, Marc Sebban
2023	—	`conf`	Predictive Modeling of Body Shape Changes in Individuals on Dietetic Treatment Using Recurrent Networks. UCAmI (2) Nahuel E. Garcia-D'Urso, Pablo Ramon Guevara, Jorge Azorín López, Marc Sebban, Amaury Habrard, Andrés Fuster Guilló
2022	J	`jnl`	Architecture for Automatic Recognition of Group Activities Using Local Motions and Context. IEEE Access Luis Felipe Borja-Borja, Jorge Azorín López, Marcelo Saval-Calvo, Andrés Fuster Guilló, Marc Sebban
2022	Misc	`conf`	Fast Multiscale Diffusion On Graphs. ICASSP Sibylle Marcotte, Amélie Barbe, Rémi Gribonval, Titouan Vayer, Marc Sebban, Pierre Borgnat, Paulo Gonçalves
2022	J	`jnl`	Learning PDE to Model Self-Organization of Matter. Entropy Eduardo Brandao, Jean-Philippe Colombier, Stefan Duffner, Rémi Emonet, Florence Garrelie, Amaury Habrard, François Jacquenet, Anthony Nakhoul, Marc Sebban
2022	J	`jnl`	MetaAP: A meta-tree-based ranking algorithm optimizing the average precision from imbalanced data. Pattern Recognit. Lett. Rémi Viola, Léo Gautheron, Amaury Habrard, Marc Sebban
2022	A*	`conf`	Optimal Tensor Transport. AAAI Tanguy Kerdoncuff, Rémi Emonet, Michaël Perrot, Marc Sebban
2022	—	`conf`	Why do State-of-the-art Super-Resolution Methods not work well for Bone Microstructure CT Imaging? EUSIPCO Rehan Jhuboo, Ievgen Redko, Alain Guignandon, Françoise Peyrin, Marc Sebban
2021	J	`jnl`	A Nearest Neighbor Algorithm for Imbalanced Classification. Int. J. Artif. Intell. Tools Rémi Viola, Rémi Emonet, Amaury Habrard, Guillaume Metzler, Sébastien Riou, Marc Sebban
2021	J	`jnl`	Fast Multiscale Diffusion on Graphs. CoRR Sibylle Marcotte, Amélie Barbe, Rémi Gribonval, Titouan Vayer, Marc Sebban, Pierre Borgnat, Paulo Gonçalves
2021	J	`jnl`	Iterative multilinear optimization for planar model fitting under geometric constraints. PeerJ Comput. Sci. Jorge Azorín López, Marc Sebban, Andrés Fuster Guilló, Marcelo Saval-Calvo, Amaury Habrard
2021	B	`conf`	Optimization of the Diffusion Time in Graph Diffused-Wasserstein Distances: Application to Domain Adaptation. ICTAI Amélie Barbe, Paulo Gonçalves, Marc Sebban, Pierre Borgnat, Rémi Gribonval, Titouan Vayer
2021	J	`jnl`	Sampled Gromov Wasserstein. Mach. Learn. Tanguy Kerdoncuff, Rémi Emonet, Marc Sebban
2020	A*	`conf`	A Swiss Army Knife for Minimax Optimal Transport. ICML Sofien Dhouib, Ievgen Redko, Tanguy Kerdoncuff, Rémi Emonet, Marc Sebban
2020	J	`jnl`	A survey on domain adaptation theory. CoRR Ievgen Redko, Emilie Morvant, Amaury Habrard, Marc Sebban, Younès Bennani
2020	—	`conf`	Graph Diffusion Wasserstein Distances. ECML/PKDD (2) Amélie Barbe, Marc Sebban, Paulo Gonçalves, Pierre Borgnat, Rémi Gribonval
2020	—	`conf`	Landmark-Based Ensemble Learning with Random Fourier Features and Gradient Boosting. ECML/PKDD (3) Léo Gautheron, Pascal Germain, Amaury Habrard, Guillaume Metzler, Emilie Morvant, Marc Sebban, Valentina Zantedeschi
2020	A*	`conf`	Learning from Few Positives: a Provably Accurate Metric Learning Algorithm to Deal with Imbalanced Data. IJCAI Rémi Viola, Rémi Emonet, Amaury Habrard, Guillaume Metzler, Marc Sebban
2020	J	`jnl`	Metric Learning from Imbalanced Data with Generalization Guarantees. Pattern Recognit. Lett. Léo Gautheron, Amaury Habrard, Emilie Morvant, Marc Sebban
2020	A*	`conf`	Metric Learning in Optimal Transport for Domain Adaptation. IJCAI Tanguy Kerdoncuff, Rémi Emonet, Marc Sebban
2019	B	`conf`	An Adjusted Nearest Neighbor Algorithm Maximizing the F-Measure from Imbalanced Data. ICTAI Rémi Viola, Rémi Emonet, Amaury Habrard, Guillaume Metzler, Sébastien Riou, Marc Sebban
2019	J	`jnl`	An Adjusted Nearest Neighbor Algorithm Maximizing the F-Measure from Imbalanced Data. CoRR Rémi Viola, Rémi Emonet, Amaury Habrard, Guillaume Metzler, Sébastien Riou, Marc Sebban
2019	J	`jnl`	Deep multi-Wasserstein unsupervised domain adaptation. Pattern Recognit. Lett. Tien-Nam Le, Amaury Habrard, Marc Sebban
2019	A*	`conf`	Differentially Private Optimal Transport: Application to Domain Adaptation. IJCAI Nam Lê Tien, Amaury Habrard, Marc Sebban
2019	A	`conf`	From Cost-Sensitive to Tight F-measure Bounds. AISTATS Kevin Bascol, Rémi Emonet, Élisa Fromont, Amaury Habrard, Guillaume Metzler, Marc Sebban
2019	J	`jnl`	Learning Landmark-Based Ensembles with Random Fourier Features and Gradient Boosting. CoRR Léo Gautheron, Pascal Germain, Amaury Habrard, Emilie Morvant, Marc Sebban, Valentina Zantedeschi
2019	B	`conf`	Metric Learning from Imbalanced Data. ICTAI Léo Gautheron, Amaury Habrard, Emilie Morvant, Marc Sebban
2019	J	`jnl`	Metric Learning from Imbalanced Data. CoRR Léo Gautheron, Emilie Morvant, Amaury Habrard, Marc Sebban
2019	J	`jnl`	On the analysis of adaptability in multi-source domain adaptation. Mach. Learn. Ievgen Redko, Amaury Habrard, Marc Sebban
2018	—	`conf`	Fast and Provably Effective Multi-view Classification with Landmark-Based SVM. ECML/PKDD (2) Valentina Zantedeschi, Rémi Emonet, Marc Sebban
2018	J	`jnl`	Learning maximum excluding ellipsoids from imbalanced data with theoretical guarantees. Pattern Recognit. Lett. Guillaume Metzler, Xavier Badiche, Brahim Belkasmi, Élisa Fromont, Amaury Habrard, Marc Sebban
2018	—	`conf`	Non-Linear Gradient Boosting for Class-Imbalance Learning. LIDTA@ECML/PKDD Jordan Fréry, Amaury Habrard, Marc Sebban, Liyun He-Guelton
2018	B	`conf`	Online Non-linear Gradient Boosting in Multi-latent Spaces. IDA Jordan Fréry, Amaury Habrard, Marc Sebban, Olivier Caelen, Liyun He-Guelton
2018	B	`conf`	Tree-Based Cost Sensitive Methods for Fraud Detection in Imbalanced Data. IDA Guillaume Metzler, Xavier Badiche, Brahim Belkasmi, Élisa Fromont, Amaury Habrard, Marc Sebban
2017	—	`conf`	Efficient Top Rank Optimization with Gradient Boosting for Supervised Anomaly Detection. ECML/PKDD (1) Jordan Fréry, Amaury Habrard, Marc Sebban, Olivier Caelen, Liyun He-Guelton
2017	J	`jnl`	L CoRR Valentina Zantedeschi, Rémi Emonet, Marc Sebban
2017	—	`conf`	Theoretical Analysis of Domain Adaptation with Optimal Transport. ECML/PKDD (2) Ievgen Redko, Amaury Habrard, Marc Sebban
2017	—	`ch.`	Unsupervised Domain Adaptation Based on Subspace Alignment. Domain Adaptation in Computer Vision Applications Basura Fernando, Rahaf Aljundi, Rémi Emonet, Amaury Habrard, Marc Sebban, Tinne Tuytelaars
2016	J	`jnl`	A new boosting algorithm for provably accurate unsupervised domain adaptation. Knowl. Inf. Syst. Amaury Habrard, Jean-Philippe Peyrache, Marc Sebban
2016	J	`jnl`	Learning discriminative tree edit similarities for linear classification - Application to melody recognition. Neurocomputing Aurélien Bellet, José Francisco Bernabeu, Amaury Habrard, Marc Sebban
2016	J	`jnl`	Lipschitz Continuity of Mahalanobis Distances and Bilinear Forms. CoRR Valentina Zantedeschi, Rémi Emonet, Marc Sebban
2016	A*	`conf`	Metric Learning as Convex Combinations of Local Models with Generalization Guarantees. CVPR Valentina Zantedeschi, Rémi Emonet, Marc Sebban
2016	J	`jnl`	Scene classification based on semantic labeling. Adv. Robotics José Carlos Rangel, Miguel Cazorla, Ismael García-Varea, Jesus Martínez-Gómez, Élisa Fromont, Marc Sebban
2016	J	`jnl`	Similarity Learning for Time Series Classification. CoRR Maria-Irina Nicolae, Éric Gaussier, Amaury Habrard, Marc Sebban
2016	J	`jnl`	Theoretical Analysis of Domain Adaptation with Optimal Transport. CoRR Ievgen Redko, Amaury Habrard, Marc Sebban
2016	—	`conf`	beta-risk: a New Surrogate Risk for Learning from Weakly Labeled Data. NIPS Valentina Zantedeschi, Rémi Emonet, Marc Sebban
2015	—	`conf`	Algorithmic Robustness for Semi-Supervised (ε, γ, τ) -Good Metric Learning. ICONIP (1) Maria-Irina Nicolae, Marc Sebban, Amaury Habrard, Éric Gaussier, Massih-Reza Amini
2015	—	`conf`	Algorithmic Robustness for Semi-Supervised (ε, γ, τ)-Good Metric Learning. ICLR (Workshop) Maria-Irina Nicolae, Marc Sebban, Amaury Habrard, Éric Gaussier, Massih-Reza Amini
2015	—	`conf`	Computing Image Descriptors from Annotations Acquired from External Tools. ROBOT (2) José Carlos Rangel, Miguel Cazorla, Ismael García-Varea, Jesus Martínez-Gómez, Élisa Fromont, Marc Sebban
2015	—	`conf`	Joint Semi-supervised Similarity Learning for Linear Classification. ECML/PKDD (1) Maria-Irina Nicolae, Éric Gaussier, Amaury Habrard, Marc Sebban
2015	A*	`conf`	Landmarks-based kernelized subspace alignment for unsupervised domain adaptation. CVPR Rahaf Aljundi, Rémi Emonet, Damien Muselet, Marc Sebban
2015	—	`book`	Metric Learning Aurélien Bellet, Amaury Habrard, Marc Sebban
2015	—	`conf`	Supervised spectral subspace clustering for visual dictionary creation in the context of image classification. ACPR Imtiaz Masud Ziko, Élisa Fromont, Damien Muselet, Marc Sebban
2014	J	`jnl`	Learning a priori constrained weighted majority votes. Mach. Learn. Aurélien Bellet, Amaury Habrard, Emilie Morvant, Marc Sebban
2014	—	`conf`	Modeling Perceptual Color Differences by Local Metric Learning. ECCV (5) Michaël Perrot, Amaury Habrard, Damien Muselet, Marc Sebban
2014	J	`jnl`	Subspace Alignment For Domain Adaptation. CoRR Basura Fernando, Amaury Habrard, Marc Sebban, Tinne Tuytelaars
2013	J	`jnl`	A Survey on Metric Learning for Feature Vectors and Structured Data. CoRR Aurélien Bellet, Amaury Habrard, Marc Sebban
2013	—	`conf`	Boosting for Unsupervised Domain Adaptation. ECML/PKDD (2) Amaury Habrard, Jean-Philippe Peyrache, Marc Sebban
2013	J	`jnl`	Combining Feature and Prototype Pruning by Uncertainty Minimization CoRR Marc Sebban, Richard Nock
2013	J	`jnl`	Iterative Self-Labeling Domain Adaptation for Linear Structured Image Classification. Int. J. Artif. Intell. Tools Amaury Habrard, Jean-Philippe Peyrache, Marc Sebban
2013	A*	`conf`	Unsupervised Visual Domain Adaptation Using Subspace Alignment. ICCV Basura Fernando, Amaury Habrard, Marc Sebban, Tinne Tuytelaars
2012	A*	`conf`	Discriminative feature fusion for image classification. CVPR Basura Fernando, Élisa Fromont, Damien Muselet, Marc Sebban
2012	J	`jnl`	Good edit similarity learning by loss minimization. Mach. Learn. Aurélien Bellet, Amaury Habrard, Marc Sebban
2012	A*	`conf`	Similarity Learning for Provably Accurate Sparse Linear Classification. ICML Aurélien Bellet, Amaury Habrard, Marc Sebban
2012	—	`conf`	Speeding Up Syntactic Learning Using Contextual Information. ICGI Leonor Becerra-Bonache, Élisa Fromont, Amaury Habrard, Michaël Perrot, Marc Sebban
2012	J	`jnl`	Supervised learning of Gaussian mixture models for visual vocabulary generation. Pattern Recognit. Basura Fernando, Élisa Fromont, Damien Muselet, Marc Sebban
2011	B	`conf`	An Experimental Study on Learning with Good Edit Similarity Functions. ICTAI Aurélien Bellet, Marc Sebban, Amaury Habrard
2011	B	`conf`	Domain Adaptation with Good Edit Similarities: A Sparse Way to Deal with Scaling and Rotation Problems in Image Classification. ICTAI Amaury Habrard, Jean-Philippe Peyrache, Marc Sebban
2011	—	`conf`	Learning Good Edit Similarities with Generalization Guarantees. ECML/PKDD (1) Aurélien Bellet, Amaury Habrard, Marc Sebban
2011	B	`conf`	Using the H-Divergence to Prune Probabilistic Automata. ICTAI Marc Bernard, Baptiste Jeudy, Jean-Philippe Peyrache, Marc Sebban, Franck Thollard
2010	J	`jnl`	Learning state machine-based string edit kernels. Pattern Recognit. Aurélien Bellet, Marc Bernard, Thierry Murgue, Marc Sebban
2010	—	`conf`	Weighted Symbols-Based Edit Distance for String-Structured Image Classification. ECML/PKDD (1) Cécile Barat, Christophe Ducottet, Élisa Fromont, Anne-Claire Legrand, Marc Sebban
2009	J	`jnl`	A lower bound on the sample size needed to perform a significant frequent pattern mining task. Pattern Recognit. Lett. Stéphanie Jacquemont, François Jacquenet, Marc Sebban
2009	J	`jnl`	Boosting Classifiers Built from Different Subsets of Features. Fundam. Informaticae Jean-Christophe Janodet, Marc Sebban, Henri-Maxime Suchier
2009	—	`conf`	Discovering Patterns in Flows: A Privacy Preserving Approach with the ACSM Prototype. ECML/PKDD (2) Stéphanie Jacquemont, François Jacquenet, Marc Sebban
2009	B	`conf`	Learning Constrained Edit State Machines. ICTAI Laurent Boyer, Olivier Gandrillon, Amaury Habrard, Mathilde Pellerin, Marc Sebban
2009	J	`jnl`	Mining probabilistic automata: a statistical view of sequential pattern mining. Mach. Learn. Stéphanie Jacquemont, François Jacquenet, Marc Sebban
2008	J	`jnl`	Learning probabilistic models of tree edit distance. Pattern Recognit. Marc Bernard, Laurent Boyer, Amaury Habrard, Marc Sebban
2008	—	`conf`	Melody Recognition with Learned Edit Distances. SSPR/SPR Amaury Habrard, José Manuel Iñesta Quereda, David Rizo, Marc Sebban
2008	—	`conf`	SEDiL: Software for Edit Distance Learning. ECML/PKDD (2) Laurent Boyer, Yann Esposito, Amaury Habrard, José Oncina, Marc Sebban
2007	—	`conf`	Correct your text with Google. Web Intelligence Stéphanie Jacquemont, François Jacquenet, Marc Sebban
2007	—	`conf`	Learning Metrics Between Tree Structured Data: Application to Image Recognition. ECML Laurent Boyer, Amaury Habrard, Marc Sebban
2006	—	`conf`	A Discriminative Model of Stochastic Edit Distance in the Form of a Conditional Transducer. ICGI Marc Bernard, Jean-Christophe Janodet, Marc Sebban
2006	—	`conf`	Learning Stochastic Tree Edit Distance. ECML Marc Bernard, Amaury Habrard, Marc Sebban
2006	J	`jnl`	Learning stochastic edit distance: Application in handwritten character recognition. Pattern Recognit. José Oncina, Marc Sebban
2006	B	`conf`	Sequence Mining Without Sequences: A New Way for Privacy Preserving. ICTAI Stéphanie Jacquemont, François Jacquenet, Marc Sebban
2006	—	`conf`	Using Learned Conditional Distributions as Edit Distance. SSPR/SPR José Oncina, Marc Sebban
2005	J	`jnl`	Adaptation du boosting à l'inférence grammaticale Rev. d'Intelligence Artif. Jean-Christophe Janodet, Richard Nock, Marc Sebban, Henri-Maxime Suchier
2005	—	`conf`	Constrained Sequence Mining based on Probabilistic Finite State Automata. CAP Stéphanie Jacquemont, François Jacquenet, Marc Sebban
2005	Misc	`conf`	Correction of Uniformly Noisy Distributions to Improve Probabilistic Grammatical Inference Algorithms. FLAIRS Amaury Habrard, Marc Bernard, Marc Sebban
2005	J	`jnl`	Detecting Irrelevant Subtrees to Improve Probabilistic Learning from Tree-structured Data. Fundam. Informaticae Amaury Habrard, Marc Bernard, Marc Sebban
2004	A*	`conf`	Boosting grammatical inference with confidence oracles. ICML Jean-Christophe Janodet, Richard Nock, Marc Sebban, Henri-Maxime Suchier
2004	B	`conf`	Mining Decision Rules from Deterministic Finite Automata. ICTAI François Jacquenet, Marc Sebban, Georges Valétudie
2003	J	`jnl`	A Simple Locally Adaptive Nearest Neighbor Rule With Application To Pollution Forecasting. Int. J. Pattern Recognit. Artif. Intell. Richard Nock, Marc Sebban, Didier Bernard
2003	—	`conf`	Improvement of the State Merging Rule on Noisy Data in Probabilistic Grammatical Inference. ECML Amaury Habrard, Marc Bernard, Marc Sebban
2003	—	`conf`	On Boosting Improvement: Error Reduction and Convergence Speed-Up. ECML Marc Sebban, Henri-Maxime Suchier
2003	A*	`conf`	On State Merging in Grammatical Inference: A Statistical Approach for Dealing with Noisy Data. ICML Marc Sebban, Jean-Christophe Janodet
2002	J	`jnl`	A data-mining approach to spacer oligonucleotide typing of Mycobacterium tuberculosis. Bioinform. Marc Sebban, Igor Mokrousov, Nalin Rastogi, Christophe Sola
2002	J	`jnl`	A hybrid filter/wrapper approach of feature selection using information theory. Pattern Recognit. Marc Sebban, Richard Nock
2002	—	`conf`	Boosting Density Function Estimators. ECML Franck Thollard, Marc Sebban, Philippe Ézéquel
2002	J	`jnl`	Stopping Criterion for Boosting-Based Data Reduction Techniques: from Binary to Multiclass Problem. J. Mach. Learn. Res. Marc Sebban, Richard Nock, Stéphane Lallich
2001	J	`jnl`	A Bayesian boosting theorem. Pattern Recognit. Lett. Richard Nock, Marc Sebban
2001	J	`jnl`	Advances in Adaptive Prototype Weighting and Selection. Int. J. Artif. Intell. Tools Richard Nock, Marc Sebban
2001	J	`jnl`	An improved bound on the finite-sample risk of the nearest neighbor rule. Pattern Recognit. Lett. Richard Nock, Marc Sebban
2001	A*	`conf`	Boosting Neighborhood-Based Classifiers. ICML Marc Sebban, Richard Nock, Stéphane Lallich
2001	Misc	`conf`	Improvement of Nearest-Neighbor Classifiers via Support Vector Machines. FLAIRS Marc Sebban, Richard Nock
2000	Misc	`conf`	A Boosting-Based Prototype Weighting and Selection Scheme. FLAIRS Richard Nock, Marc Sebban
2000	—	`conf`	A Symmetric Nearest Neighbor Learning Rule. EWCBR Richard Nock, Marc Sebban, Pascal Jabby
2000	A	`conf`	Combining Feature and Example Pruning by Uncertainty Minimization. UAI Marc Sebban, Richard Nock
2000	—	`conf`	Contribution of Dataset Reduction Techniques to Tree-Simplification and Knowledge Discovery. PKDD Marc Sebban, Richard Nock
2000	Misc	`conf`	Identifying and Eliminating Irrelevant Instances Using Information Theory. AI Marc Sebban, Richard Nock
2000	J	`jnl`	Impact of learning set quality and size on decision tree performances. Int. J. Comput. Syst. Signals Marc Sebban, Richard Nock, Jean-Hugues Chauchat, Ricco Rakotomalala
2000	A*	`conf`	Instance Pruning as an Information Preserving Problem. ICML Marc Sebban, Richard Nock
2000	B	`conf`	Sharper Bounds for the Hardness of Prototype and Feature Selection. ALT Richard Nock, Marc Sebban
1999	—	`conf`	Contribution of Boosting in Wrapper Models. PKDD Marc Sebban, Richard Nock
1999	—	`conf`	Experiments on a Representation-Independent "Top-Down and Prune" Induction Scheme. PKDD Richard Nock, Marc Sebban, Pascal Jappy
1999	B	`conf`	From Theoretical Learnability to Statistical Measures of the Learnable. IDA Marc Sebban, Gilles Richard
1999	—	`conf`	Selection and Statistical Validation of Features and Prototypes. PKDD Marc Sebban, Djamel A. Zighed, S. Di Palma
1998	Misc	`conf`	Prototype Selection from Homogeneous Subsets by a Monte Carlo Sampling. FLAIRS Marc Sebban
1998	—	`conf`	Strings Clustering and Statistical Validation of Clusters. Canadian AI Marc Sebban, Anne M. Landraud
1996	J	`jnl`	A Comparison of Some Contextual Discretization Methods. Inf. Sci. Sabine Rabaséda, Ricco Rakotomalala, Marc Sebban