MULTRAK: A System for Automatic Multiperson Localization and Tracking in Real-Time. - Olivier Bernier; Michel Collobert; Raphaël Féraud; Vincent Lemaire 001; Jean-Emmanuel Viallet; Daniel Collobert (ICIP (1), 1998)

A New Method to Increase the Margin of Multilayer Perceptrons. - Vincent Lemaire 001; Olivier Bernier; Daniel Collobert; Fabrice Clérot (Neural Process. Lett., 2000)

SOM-Based Clustering for On-Line Fraud Behavior Classification: A Case study. - Vincent Lemaire 001; Fabrice Clérot (FSKD, 2002)

An input variable importance definition based on empirical data probability and its use in variable selection. - Vincent Lemaire 001; Fabrice Clérot (IJCNN, 2004)

Individualized HRTFs from few measurements: a statistical learning approach. - Vincent Lemaire 001; Fabrice Clérot; Sylvain Busson; Rozenn Nicol; Vincent Choqueuse (IJCNN, 2005)

The Many Faces of a Kohonen Map A Case Study: SOM-based Clustering for On-Line Fraud Behavior Classification. - Vincent Lemaire 001; Fabrice Clérot (Classification and Clustering for Knowledge Discovery, 2005)

An Input Variable Importance Definition based on Empirical Data Probability Distribution. - Vincent Lemaire 001; Fabrice Clérot (Feature Extraction, 2006)

État de l'art sur les méthodes statistiques d'apprentissage actif. - Alexis Bondu; Vincent Lemaire 001 (AAFD, 2006)

Effective Organization and Visualization of Web Search Results. - Nicolas Bonnel 002; Vincent Lemaire 001; Alexandre Cotarmanac'h; Annie Morin (EuroIMSA, 2006)

A Statistical Approach for Learning Invariants: Application to Image Color Correction and Learning Invariants to Illumination. - Benedicte Bascle; Olivier Bernier; Vincent Lemaire 001 (ICONIP (2), 2006)

Driven Forward Features Selection: A Comparative Study on Neural Networks. - Vincent Lemaire 001; Raphaël Féraud (ICONIP (2), 2006)

Illumination-Invariant Color Image Correction. - Benedicte Bascle; Olivier Bernier; Vincent Lemaire 001 (IWICPAS, 2006)

Apprentissage actif d'émotions dans les dialogues Homme-Machine. - Alexis Bondu; Vincent Lemaire 001; Barbara Poulain (EGC, 2007)

Une méthode d'interprétation de scores. - Vincent Lemaire 001; Raphaël Féraud (EGC, 2007)

Combining Several SOM Approaches in Data Mining: Application to ADSL Customer Behaviours Analysis. - Françoise Fessant; Vincent Lemaire 001; Fabrice Clérot (GfKl, 2007)

Active Learning Strategies: A Case Study for Detection of Emotions in Speech. - Alexis Bondu; Vincent Lemaire 001; Barbara Poulain (ICDM, 2007)

Learning invariants to illumination changes typical of indoor environments: Application to image color correction. - Benedicte Bascle; Olivier Bernier; Vincent Lemaire 001 (Int. J. Imaging Syst. Technol., 2007)

Data MiningExploration, Sélection, Compréhension. - Vincent Lemaire 001 (2008)

A Non-parametric Semi-supervised Discretization Method. - Alexis Bondu; Marc Boullé; Vincent Lemaire 001; Stéphane Loiseau; Béatrice Duval (ICDM, 2008)

Adaptive curiosity for emotions detection in speech. - Alexis Bondu; Vincent Lemaire 001 (IJCNN, 2008)

Contact personalization using a score understanding method. - Vincent Lemaire 001; Raphaël Féraud; Nicolas Voisine (IJCNN, 2008)

Exploration des corrélations dans un classifieur - Application au placement d'offres commerciales. - Vincent Lemaire 001; Carine Hue (EGC, 2009)

Analysis of the KDD Cup 2009: Fast Scoring on a Large Orange Customer Database. - Isabelle Guyon; Vincent Lemaire 001; Marc Boullé; Gideon Dror; David Vogel (KDD Cup, 2009)

Design and analysis of the KDD cup 2009: fast scoring on a large orange customer database. - Isabelle Guyon; Vincent Lemaire 001; Marc Boullé; Gideon Dror; David Vogel (SIGKDD Explor., 2009)

Classification incrémentale supervisée : un panel introductif. - Christophe Salperwyck; Vincent Lemaire 001 (AAFD, 2010)

Une nouvelle stratégie d'apprentissage Bayésienne. - Alexis Bondu; Vincent Lemaire 001; Marc Boullé (EGC, 2010)

Exploration vs. exploitation in active learning : A Bayesian approach. - Alexis Bondu; Vincent Lemaire 001; Marc Boullé (IJCNN, 2010)

Design and analysis of the WCCI 2010 active learning challenge. - Isabelle Guyon; Gavin C. Cawley; Gideon Dror; Vincent Lemaire 001 (IJCNN, 2010)

A method to build a representation using a classifier and its use in a K Nearest Neighbors-based deployment. - Vincent Lemaire 001; Marc Boullé; Fabrice Clérot; Pascal Gouzien (IJCNN, 2010)

The Orange Customer Analysis Platform. - Raphaël Féraud; Marc Boullé; Fabrice Clérot; Françoise Fessant; Vincent Lemaire 001 (ICDM, 2010)

A non-parametric semi-supervised discretization method. - Alexis Bondu; Marc Boullé; Vincent Lemaire 001 (Knowl. Inf. Syst., 2010)

Unsupervised and transfer learning challenge. - Isabelle Guyon; Gideon Dror; Vincent Lemaire 001; Graham W. Taylor; David W. Aha (IJCNN, 2011)

Learning with few examples: An empirical study on leading classifiers. - Christophe Salperwyck; Vincent Lemaire 001 (IJCNN, 2011)

Results of the Active Learning Challenge. - Isabelle Guyon; Gavin C. Cawley; Gideon Dror; Vincent Lemaire 001 (Active Learning and Experimental Design @ AISTATS, 2011)

K-moyennes contraintes par un classifieur. Application à la personnalisation de scores de campagnes. - Vincent Lemaire 001; Nicolas Creff; Fabrice Clérot (EGC, 2012)

ICML2011 Unsupervised and Transfer Learning Workshop. - Daniel L. Silver; Isabelle Guyon; Graham W. Taylor; Gideon Dror; Vincent Lemaire 001 (ICML Unsupervised and Transfer Learning, 2012)

Analysis of the IJCNN 2011 UTL challenge. - Isabelle Guyon; Gideon Dror; Vincent Lemaire 001; Daniel L. Silver; Graham W. Taylor; David W. Aha (Neural Networks, 2012)

Nomao. - Laurent Candillier; Vincent Lemaire 001 (UCI Machine Learning Repository, 2012)

Incremental Weighted Naive Bays Classifiers for Data Stream. - Christophe Salperwyck; Vincent Lemaire 001; Carine Hue (ECDA, 2013)

Grille bivariée pour la détection de changement dans un flux étiqueté. - Christophe Salperwyck; Marc Boullé; Vincent Lemaire 001 (EGC, 2013)

Active learning in the real-world design and analysis of the Nomao challenge. - Laurent Candillier; Vincent Lemaire 001 (IJCNN, 2013)

Incremental decision tree based on order statistics. - Christophe Salperwyck; Vincent Lemaire 001 (IJCNN, 2013)

A Two Layers Incremental Discretization Based on Order Statistics. - Christophe Salperwyck; Vincent Lemaire 001 (Statistical Models for Data Analysis, 2013)

A Survey on Supervised Classification on Data Streams. - Vincent Lemaire 001; Christophe Salperwyck; Alexis Bondu (eBISS, 2014)

Supervised Pre-processings Are Useful for Supervised Clustering. - Oumaima Alaoui Ismaili; Vincent Lemaire 001; Antoine Cornuéjols (ECDA, 2014)

First Connectomics Challenge: From Imaging to Connectivity. - Javier G. Orlandi; Bisakha Ray; Demian Battaglia; Isabelle Guyon; Vincent Lemaire 001; Mehreen Saeed; Alexander R. Statnikov; Olav Stetter; Jordi Soriano (Neural Connectomics, 2014)

Apprentissage incrémental anytime d'un classifieur Bayésien naïf pondéré. - Carine Hue; Marc Boullé; Vincent Lemaire 001 (EGC, 2014)

Classifieur naïf de Bayes pondéré pour flux de données. - Christophe Salperwyck; Vincent Lemaire 001; Carine Hue (EGC, 2014)

A Supervised Methodology to Measure the Variables Contribution to a Clustering. - Oumaima Alaoui Ismaili; Vincent Lemaire 001; Antoine Cornuéjols (ICONIP (1), 2014)

Design of the first neuronal connectomics challenge: From imaging to connectivity. - Isabelle Guyon; Demian Battaglia; Alice Guyon; Vincent Lemaire 001; Javier G. Orlandi; Bisakha Ray; Mehreen Saeed; Jordi Soriano; Alexander R. Statnikov; Olav Stetter (IJCNN, 2014)

Open challenges for data stream mining research. - Georg Krempl; Indre Zliobaite; Dariusz Brzezinski; Eyke Hüllermeier; Mark Last; Vincent Lemaire 001; Tino Noack; Ammar Shaker; Sonja Sievi; Myra Spiliopoulou; Jerzy Stefanowski (SIGKDD Explor., 2014)

Online Learning of a Weighted Selective Naive Bayes Classifier with Non-convex Optimization. - Carine Hue; Marc Boullé; Vincent Lemaire 001 (EGC (best of volume), 2015)

Feedback - Study and Improvement of the Random Forest of the Mahout library in the context of marketing data of Orange. - Cedric Thao; Nicolas Voisine; Vincent Lemaire 001; Romain Trinquart (EGC, 2015)

An initialization scheme for supervized K-means. - Vincent Lemaire 001; Oumaima Alaoui Ismaili; Antoine Cornuéjols (IJCNN, 2015)

Concept drift detection using supervised bivariate grids. - Christophe Salperwyck; Marc Boullé; Vincent Lemaire 001 (IJCNN, 2015)

How to select information that matters: a comparative study on active learning strategies for classification. - Christian Beyer; Georg Krempl; Vincent Lemaire 001 (I-KNOW, 2015)

Increasing loyalty using predictive modeling in Business-to-Business Telecommunication. - Patrick Luciano; Ismail Rebai; Vincent Lemaire 001 (CoRR, 2015)

Optimised probabilistic active learning (OPAL) - For fast, non-myopic, cost-sensitive active classification. - Georg Krempl; Daniel Kottke; Vincent Lemaire 001 (Mach. Learn., 2015)

Analyse exploratoire par k-Coclustering avec Khiops CoViz. - Bruno Guerraz; Marc Boullé; Dominique Gay; Vincent Lemaire 001; Fabrice Clérot (EGC, 2016)

Une méthode supervisée pour initialiser les centres des K-moyennes. - Oumaima Alaoui Ismaili; Vincent Lemaire 001; Antoine Cornuéjols (EGC, 2016)

Improving the Prediction Cost of Drift Handling Algorithms by Abstaining. - Pierre-Xavier Loeffel; Vincent Lemaire 001; Christophe Marsala; Marcin Detyniecki (ICDM Workshops, 2016)

Proactive Fiber Damage Detection in Real-time Coherent Receiver. - Fabien Boitier; Vincent Lemaire 001; Jelena Pesic; Lucia Chavarría; Patricia Layec; Sébastien Bigo; Eric Dutisseuil (ECOC, 2017)

Un critère d'évaluation pour les K-moyennes prédictives. - Oumaima Alaoui Ismaili; Vincent Lemaire 001; Antoine Cornuéjols (EGC, 2017)

Seamless Optical Path Restoration with Just-in-Time Resource Allocation Leveraging Machine Learning. - Fabien Boitier; Jelena Pesic; Vincent Lemaire 001; Eric Dutisseuil; José Manuel Estarán Tolosa; Philippe Jennevé; Nicolas Le Moing; Haïk Mardoyan; Patricia Layec (ECOC, 2018)

Apport des modèles locaux pour les K-moyennes prédictives. - Vincent Lemaire 001; Oumaima Alaoui Ismaili (EGC, 2018)

PerForecast : un outil de prévision de l'évolution de séries temporelles pour le planning capacitaire. - Colin Leverger; Régis Marguerie; Vincent Lemaire 001; Thomas Guyet; Simon Malinowski (EGC, 2018)

Day-ahead time series forecasting: application to capacity planning. - Colin Leverger; Vincent Lemaire 001; Simon Malinowski; Thomas Guyet; Laurence Rozé (CoRR, 2018)

FEARS: a Feature and Representation Selection approach for Time Series Classification. - Alexis Bondu; Dominique Gay; Vincent Lemaire 001; Marc Boullé; Eole Cervenka (ACML, 2019)

Apprentissage fédératif pour la prédiction du churn : une évaluation. - Sébastien Godard; Nicolas Voisine; Tanguy Urvoy; Vincent Lemaire 001 (EGC, 2019)

Toward a Framework for Seasonal Time Series Forecasting Using Clustering. - Colin Leverger; Simon Malinowski; Thomas Guyet; Vincent Lemaire 001; Alexis Bondu; Alexandre Termier (IDEAL (1), 2019)

Proactive Fiber Break Detection Based on Quaternion Time Series and Automatic Variable Selection from Relational Data. - Vincent Lemaire 001; Fabien Boitier; Jelena Pesic; Alexis Bondu; Stéphane Ragot; Fabrice Clérot (AALTD@PKDD/ECML, 2019)

Graph2Bots, Unsupervised Assistance for Designing Chatbots. - Jean Léon Bouraoui; Sonia Le Meitour; Romain Carbou; Lina Maria Rojas-Barahona; Vincent Lemaire 001 (SIGdial, 2019)

Should we Reload Time Series Classification Performance Evaluation ? (a position paper). - Dominique Gay; Vincent Lemaire 001 (CoRR, 2019)

Multivariate Time Series Classification: A Relational Way. - Dominique Gay; Alexis Bondu; Vincent Lemaire 001; Marc Boullé; Fabrice Clérot (DaWaK, 2020)

Sélections simultanées de variables et de représentations pour la classification de séries temporelles. - Alexis Bondu; Dominique Gay; Vincent Lemaire 001; Marc Boullé; Eole Cervenka (EGC, 2020)

Apprentissage par renforcement de stratégies d'apprentissage actif : une évaluation. - Louis Desreumaux; Vincent Lemaire 001 (EGC, 2020)

Learning Active Learning at the Crossroads? Evaluation and Discussion. - Louis Desreumaux; Vincent Lemaire 001 (IAL@PKDD/ECML, 2020)

Importance Reweighting for Biquality Learning. - Pierre Nodet; Vincent Lemaire 001; Alexis Bondu; Antoine Cornuéjols (CoRR, 2020)

On the intrinsic robustness of some leading classifiers and symetric loss function - an empirical evaluation. - Hugo Le Baher; Vincent Lemaire 001; Romain Trinquart (CoRR, 2020)

Predictive K-means with local models. - Vincent Lemaire 001; Oumaima Alaoui Ismaili; Antoine Cornuéjols; Dominique Gay (CoRR, 2020)

From Weakly Supervised Learning to Biquality Learning, a brief introduction. - Pierre Nodet; Vincent Lemaire 001; Alexis Bondu; Antoine Cornuéjols; Adam Ouorou (CoRR, 2020)

Early Classification of Time Series: Cost-based multiclass Algorithms. - Paul-Emile Zafar; Youssef Achenchabe; Alexis Bondu; Antoine Cornuéjols; Vincent Lemaire 001 (DSAA, 2021)

Importance Reweighting for Biquality Learning. - Pierre Nodet; Vincent Lemaire 001; Alexis Bondu; Antoine Cornuéjols; Adam Ouorou (IJCNN, 2021)

From Weakly Supervised Learning to Biquality Learning: an Introduction. - Pierre Nodet; Vincent Lemaire 001; Alexis Bondu; Antoine Cornuéjols; Adam Ouorou (IJCNN, 2021)

Multi-Label kNN classifier with Online Dual Memory on data stream. - Xihui Wang; Pascale Kuntz; Frank Meyer; Vincent Lemaire 001 (ICDM (Workshops), 2021)

Interpretable Feature Construction for Time Series Extrinsic Regression. - Dominique Gay; Alexis Bondu; Vincent Lemaire 001; Marc Boullé (PAKDD (1), 2021)

Contrastive Representations for Label Noise Require Fine-Tuning. - Pierre Nodet; Vincent Lemaire 001; Alexis Bondu; Antoine Cornuéjols (IAL@PKDD/ECML, 2021)

Evidential Nearest Neighbours in Active Learning. - Daniel Zhu; Arnaud Martin 001; Yolande Le Gall; Jean-Christophe Dubois; Vincent Lemaire 001 (IAL@PKDD/ECML, 2021)

Early Classification of Time Series is Meaningful. - Youssef Achenchabe; Alexis Bondu; Antoine Cornuéjols; Vincent Lemaire 001 (CoRR, 2021)

Construction de variables à l'aide de classifieurs comme aide à la régression. - Colin Troisemaine; Vincent Lemaire 001 (CoRR, 2021)

When to Classify Events in Open Times Series? - Youssef Achenchabe; Alexis Bondu; Antoine Cornuéjols; Vincent Lemaire 001 (ACML, 2022)

Progressive prediction of hospitalisation and patient disposition in the emergency department. - Laura Uhl; Vincent Augusto; Vincent Lemaire 001; Youenn Alexandre; Fanny Jardinaud; Paolo Bercelli; Saber Aloui (IEEE Big Data, 2022)

Repondération Préférentielle pour l'Apprentissage Biqualité. - Pierre Nodet; Vincent Lemaire 001; Alexis Bondu; Antoine Cornuéjols (EGC, 2022)

Construction de variables à l'aide de classifieurs comme aide à la régression : une évaluation empirique. - Colin Troisemaine; Vincent Lemaire 001 (EGC, 2022)

A Method for Discovering Novel Classes in Tabular Data. - Colin Troisemaine; Joachim Flocon-Cholet; Stéphane Gosselin; Sandrine Vaton; Alexandre Reiffers-Masson; Vincent Lemaire 001 (ICKG, 2022)

Early and Revocable Time Series Classification. - Youssef Achenchabe; Alexis Bondu; Antoine Cornuéjols; Vincent Lemaire 001 (IJCNN, 2022)

ECOTS: Early Classification in Open Time Series. - Youssef Achenchabe; Alexis Bondu; Antoine Cornuéjols; Vincent Lemaire 001 (CoRR, 2022)

Open challenges for Machine Learning based Early Decision-Making research. - Alexis Bondu; Youssef Achenchabe; Albert Bifet; Fabrice Clérot; Antoine Cornuéjols; João Gama 001; Georges Hébrail; Vincent Lemaire 001; Pierre-Francois Marteau (SIGKDD Explor., 2022)

Human Activity Segmentation Challenge @ ECML/PKDD'23. - Arik Ermshaus; Patrick Schäfer 001; Anthony J. Bagnall; Thomas Guyet; Georgiana Ifrim; Vincent Lemaire 001; Ulf Leser; Colin Leverger; Simon Malinowski (AALTD@ECML/PKDD, 2023)

Comparaison des valeurs de Shapley et des valeurs du poids de l'évidence dans le cas du classifieur naïf de Bayes. - Vincent Lemaire 001; Fabrice Clérot; Marc Boullé (EGC, 2023)

Découvrir de nouvelles classes dans des données tabulaires. - Colin Troisemaine; Joachim Flocon-Cholet; Stéphane Gosselin; Sandrine Vaton; Alexandre Reiffers-Masson; Vincent Lemaire 001 (EGC, 2023)

Automatic Feature Engineering for Time Series Classification: Evaluation and Discussion. - Aurélien Renault; Alexis Bondu; Vincent Lemaire 001; Dominique Gay (IJCNN, 2023)

An Efficient Shapley Value Computation for the Naive Bayes Classifier. - Vincent Lemaire 001; Fabrice Clérot; Marc Boullé (PKDD/ECML Workshops (1), 2023)

An Interactive Interface for Novel Class Discovery in Tabular Data. - Colin Troisemaine; Joachim Flocon-Cholet; Stéphane Gosselin; Alexandre Reiffers-Masson; Sandrine Vaton; Vincent Lemaire 001 (ECML/PKDD (7), 2023)

Novel Class Discovery: an Introduction and Key Concepts. - Colin Troisemaine; Vincent Lemaire 001; Stéphane Gosselin; Alexandre Reiffers-Masson; Joachim Flocon-Cholet; Sandrine Vaton (CoRR, 2023)

biquality-learn: a Python library for Biquality Learning. - Pierre Nodet; Vincent Lemaire 001; Alexis Bondu; Antoine Cornuéjols (CoRR, 2023)

Viewing the process of generating counterfactuals as a source of knowledge - Application to the Naive Bayes classifier. - Vincent Lemaire 001; Nathan Le Boudec; Françoise Fessant; Victor Guyomard (CoRR, 2023)

Evidential uncertainties on rich labels for active learning. - Arthur Hoarau; Vincent Lemaire 001; Arnaud Martin 001; Jean-Christophe Dubois; Yolande Le Gall (CoRR, 2023)

Biquality learning: a framework to design algorithms dealing with closed-set distribution shifts. - Pierre Nodet; Vincent Lemaire 001; Alexis Bondu; Antoine Cornuéjols (Mach. Learn., 2023)

COCALITE: A Hybrid Model COmbining CAtch22 and LITE for Time Series Classification. - Oumaima Badi; Maxime Devanne; Ali Ismail-Fawaz; Javidan Abdullayev; Vincent Lemaire 001; Stefano Berretti; Jonathan Weber; Germain Forestier (IEEE Big Data, 2024)

Voir le processus de création d'exemples contrefactuels comme une source de connaissance - Application au classifieur Naïf de Bayes. - Vincent Lemaire 001; Nathan Le Boudec; Françoise Fessant; Victor Guyomard (EGC, 2024)

Méthode crédibiliste pour l'extraction d'incertitudes sans dépendance aux observations. - Arthur Hoarau; Vincent Lemaire 001; Arnaud Martin 001; Jean-Christophe Dubois; Yolande Le Gall (EGC, 2024)

Viewing the process of generating counterfactuals as a source of knowledge: a new approach for explaining classifiers. - Vincent Lemaire 001; Nathan Le Boudec; Victor Guyomard; Françoise Fessant (IJCNN, 2024)

Constructing Variables Using Classifiers as an Aid to Regression: An Empirical Assessment. - Colin Troisemaine; Vincent Lemaire 001 (CoRR, 2024)

Early Classification of Time Series: Taxonomy and Benchmark. - Aurélien Renault; Alexis Bondu; Antoine Cornuéjols; Vincent Lemaire 001 (CoRR, 2024)

ml_edm package: a Python toolkit for Machine Learning based Early Decision Making. - Aurélien Renault; Youssef Achenchabe; Edouard Bertrand; Alexis Bondu; Antoine Cornuéjols; Vincent Lemaire 001; Asma Dachraoui (CoRR, 2024)

DEMAU: Decompose, Explore, Model and Analyse Uncertainties. - Arthur Hoarau; Vincent Lemaire 001 (CoRR, 2024)

Mislabeled examples detection viewed as probing machine learning models: concepts, survey and extensive benchmark. - Thomas George; Pierre Nodet; Alexis Bondu; Vincent Lemaire 001 (Trans. Mach. Learn. Res., 2024)

A practical approach to novel class discovery in tabular data. - Colin Troisemaine; Alexandre Reiffers-Masson; Stéphane Gosselin; Vincent Lemaire 001; Sandrine Vaton (Data Min. Knowl. Discov., 2024)

Evidential uncertainty sampling strategies for active learning. - Arthur Hoarau; Vincent Lemaire 001; Yolande Le Gall; Jean-Christophe Dubois; Arnaud Martin 001 (Mach. Learn., 2024)

Khiops: apprentissage automatique sans hyperparamètre. - Marc Boullé; Nicolas Voisine; Bruno Guerraz; Carine Hue; Felipe Olmos; Vladimir Popescu; Stéphane Gouache; Stéphane Bouget; Alexis Bondu; Luc-Aurélien Gauthier; Noureddine Yassine Nair Benrekia; Fabrice Clérot; et al. (EGC, 2025)

Calibration des modèles d'apprentissage pour l'amélioration des détecteurs automatiques d'exemples mal-étiquetés. - Ilies Chibane; Thomas George; Pierre Nodet; Vincent Lemaire 001 (EGC, 2025)

Construction non-supervisée de variables pour la détection d'anomalies dans les séries temporelles. - Marine Hamon; Vincent Lemaire 001; Noureddine Yassine Nair Benrekia; Samuel Berlemont; Julien Cumin (EGC, 2025)

DEMAU: Decompose, Explore, Model & Analyse Uncertainties. - Arthur Hoarau; Vincent Lemaire 001 (EGC, 2025)

Apprentissage multi-labels et multi-tâches en continu pour données tabulaires: proposition d'un protocole de création de tâches et évaluation de classifieurs. - Hugo Peuzet; Pascale Kuntz; Frank Meyer; Vincent Lemaire 001; Killian Le Mau (EGC, 2025)

Unsupervised Feature Construction for Anomaly Detection in Time Series - An Evaluation. - Marine Hamon; Vincent Lemaire 001; Noureddine Yassine Nair Benrekia; Samuel Berlemont; Julien Cumin (CoRR, 2025)

Deep Reinforcement Learning based Triggering Function for Early Classifiers of Time Series. - Aurélien Renault; Alexis Bondu; Antoine Cornuéjols; Vincent Lemaire 001 (CoRR, 2025)

Frugal AI: Introduction, Concepts, Development and Open Questions. - Ludovic Arga; François Bélorgey; Arnaud Braud; Romain Carbou; Nathalie Charbonniaud; Catherine Colomes; Lionel Delphin-Poulat; David Excoffier; Christel Fauché; Thomas George; Frédéric Guyard; Thomas Hassan; et al. (SIGKDD Explor., 2025)