Vincent Lemaire

Publications

Invited Talks

Acknowledgements

[2024] Mislabeled examples detection viewed as probing machine learning models: concepts, survey and extensive benchmark, Thomas George, Pierre Nodet, Alexis Bondu, Vincent Lemaire , in Transactions on Machine Learning Research (TMLR)
[2024] DEMAU: Decompose, Explore, Model and Analyse Uncertainties, Arthur Hoarau, Vincent Lemaire, in arXiv preprint arXiv:2409.08105
[2024] ml_edm package: a Python toolkit for Machine Learning based Early Decision Making, Aurélien Renault, Youssef Achenchabe, Édouard Bertrand, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire, Asma Dachraoui, in arXiv preprint arXiv:2408.12925
[2024] "A Practical Approach to Novel Class Discovery in Tabular Data", Colin Troisemaine, Alexandre Reiffers-Masson, Stéphane Gosselin, Vincent Lemaire, Sandrine Vaton, in arXiv preprint arXiv:2311.05440, then is the journal track "Data Mining and Knowledge Discovery" (DMKD 2024) of the conference ECML PKDD 2024.
[2024] "Evidential uncertainty sampling strategies for active learning", Arthur Hoarau, Vincent Lemaire, Arnaud Martin, Jean-Chrisstophe Dubois, Yollande Le Gall, arXiv preprint arXiv:2309.12494, then is the journal track "Machine Learning" (ML 2024) of the conference ECML PKDD 2024.
[2024] "Viewing the process of generating counterfactuals as a source of knowledge: a new approach for explaining classifiers", Vincent Lemaire, Nathan Le Boudec, Victor Guyomard, Françoise Fessant, in arXiv preprint arXiv:2309.04284 then in the conference International Joint Conference on Neural Networks (IJCNN 2024).
[2024] "Early Classification of Time Series: Taxonomy and Benchmark", A Renault, A Bondu, A Cornuéjols, V Lemaire, in arXiv preprint arXiv:2406.18332
[2024] "Méthodes crédibilistes pour l'extraction d'incertitudes sans dépendance aux observations", Arthur Hoarau, Vincent Lemaire, Arnaud Martin, Jean-Christophe Dubois and Yolande Le Gall, in Extraction et Gestion des Connaissances (EGC 2024)
[2024] "Voir le processus de création d'exemples contrefactuels comme une source de connaissance - Application au classifieur Naïf de Bayes", Vincent Lemaire, Nathan Le Boudec, Victor Guyomard and Francoise Fessant, in Extraction et Gestion des Connaissances (EGC 2024)

[2023] "Human Activity Segmentation Challenge", Arik Ermshaus, Patrick Schäfer, Ulf Leser, Anthony Bagnall, Romain Tavenard, Colin Leverger, Vincent Lemaire, Simon Malinowski, Thomas Guyet, Georgiana Ifrim, in European Conference on Machine Learning (ECML 2023)
[2023] "Biquality learning: a framework to design algorithms dealing with closed-set distribution shifts" , Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols, in Machine Learning journal
[2023] "Biquality-learn: a Python library for Biquality Learning", Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols, arXiv preprint arXiv:2308.09643
[2023] "An Efficient Shapley Value Computation for the Naive Bayes Classifier", Vincent Lemaire, Fabrice Clérot, Marc Boullé, in European Conference on Machine Learning (ECML PKDD) - Workshop AIMLAI (Advances in Interpretable Machine Learning and Artificial Intelligence), At: Torino
[2023] "Automatic Feature Engineering for Time Series Classification: Evaluation and Discussion", Aurélien Renault, Alexis Bondu, Vincent Lemaire, Dominique Gay, International Joint Conference on Neural Networks (IJCNN 2023)
[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, European Conference on Machine Learning (Demo), arXiv preprint arXiv:2306.12919
[2023] "Probabilistic forecasting of seasonal time series, Combining clustering and classification for forecasting", Colin Leverger, Thomas Guyet, Simon Malinowski, Vincent Lemaire, Alexis Bondu, Laurence Rozé, Alexandre Termier, Régis Marguerie, Theory and Applications of Time Series Analysis and Forecasting: Selected Contributions from ITISE 2021
[2023] "Novel Class Discovery: an Introduction and Key Concepts", Colin Troisemaine, Vincent Lemaire, Stéphane Gosselin, Alexandre Reiffers-Masson, Joachim Flocon-Cholet, Sandrine Vaton, arXiv preprint arXiv:2302.12028
[2023] "Défi TextMine'23-Reconnaissance d'entités d'intérêts dans les signatures d'e-mails", Kévin Cousot, Cédric Lopez, Pascal Cuxac, Vincent Lemaire - Atelier TextMine'23, Extraction et Gestion des Connaissances: EGC'2023
[2023] "Découvrir de nouvelles classes dans des données tabulaires", Colin Troisemaine, Joachim Flocon-Cholet, Stéphane Gosselin, Sandrine Vaton, Alexandre Reiffers-Masson, Vincent Lemaire Extraction et Gestion des Connaissances: EGC'2023
[2023] "Comparaison des valeurs de Shapley et des valeurs du poids de l’évidence dans le cas du classifieur naïf de Bayes", Vincent Lemaire, Fabrice Clérot, Marc Boullé, Extraction et Gestion des Connaissances: EGC'2023

[2022] "Progressive prediction of hospitalisation and patient disposition in the emergency department”, Laura Uhl, Vincent Augusto, Vincent Lemaire, Youenn Alexandre, Fanny Jardinaud, Paolo Bercelli, and Saber Aloui IEEE International Conference on Big Data 2022
[2022] "When to Classify Events in Open Times Series?" Y Achenchabe, A Bondu, A Cornuéjols, V Lemaire Asian Conference on Machine Learning (ACML)
[2022] "A Method for Discovering Novel Classes in Tabular Data", Colin Troisemaine, Joachim Flocon-Cholet, Stéphane Gosselin, Sandrine Vaton, Alexandre Reiffers-Masson, Vincent Lemaire, in IEEE International Conference on Knowledge Graph (ICKG)
[2022] "Open challenges for Machine Learning based Early Decision-Making research", Alexis Bondu, Youssef Achenchabe, Albert Bifet, Fabrice Clérot, Antoine Cornuéjols, Joao Gama, Georges Hébrail, Vincent Lemaire, Pierre-François Marteau, to appear in SIGKDD explorations (december 2022)
[2022] "Early and Revocable Time Series Classification" Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire, IEEE WCCI-IJCNN, International Joint Conference on Neural Networks
[2022] "Repondération Préférentielle pour l’Apprentissage Biqualité" Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols, Extraction et Gestion des Connaissances: EGC'2022
[2022] "Construction de variables à l’aide de classifieurs comme aide à la régression: une évaluation empirique Colin Troisemaine, Vincent Lemaire, Extraction et Gestion des Connaissances: EGC'2022

[2021] "Early and Revocable Time Series Classification" Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire arXiv preprint arXiv:2109.10285
[2021] "Multi-Label kNN classifier with Online Dual Memory on data stream", Xihui Wang, Pascale Kuntz, Frank Meyer, Vincent Lemaire, IEEE ICDM, IEEE International Conference on Data Mining, Workshop IncrLearn
[2021] "Evidential Nearest Neighbours in Active Learning", Daniel Zhu, Arnaud Martin, Jean-Christophe Dubois, Yolande Le Gall and Vincent Lemaire, ECML PKDD 2021, Workshop "Interactive Adaptive Learning (IAL), Bilbao
[2021] "Early Classification of Time Series: Cost-based multiclass Algorithms", Paul-Emile Zafar, Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire IEEE International Conference on Data Science and Advanced Analytics (DSAA 2021)
[2021] "Contrastive Representations for Label Noise Require Fine-Tuning", Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols, ECML PKDD 2021, Workshop "Interactive Adaptive Learning (IAL), Bilbao
[2021] "Modèle crédibiliste pour l'échantillonnage en apprentissage actif", Daniel Zhu, Arnaud Martin, Jean-Christophe Dubois, Yolande Le Gall and Vincent Lemaire, Rencontres francophones sur la logique floue et ses applications, (LFA 2021)
[2021] “Probabilistic forecasting of seasonal time series - Combining clustering and classification for forecasting”, Colin Leverger, Thomas Guyet, Simon Malinowski, Vincent Lemaire, Alexis Bondu, Laurence Roze, Alexandre Termier and Régis Marguerie, International conference on Time Series and Forecasting (ITISE 2021)
[2021] “Interpretable Feature Construction for Time Series Extrinsic Regression”, Dominique Gay, Alexis Bondu, Vincent Lemaire, Marc Boullé, in Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2021) - (preprint arXiv:2103.10247)
[2021] "From Weakly Supervised Learning to Biquality Learning, an Introduction", Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols and Adam Ouorou, International Joint Conference on Neural Networks (IJCNN 2021) - (preprint arXiv:2012.09632)
[2021] "Importance Reweighting for Biquality Learning", P Nodet, V Lemaire, A Bondu, A Cornuéjols, International Joint Conference on Neural Networks (IJCNN 2021) - (preprint arXiv:2010.09621)
[2021] "On the intrinsic robustness to noise of some leading classifiers and symmetric loss function--an empirical evaluation", H Le Baher, V Lemaire, R Trinquart, International Workshop on Data Quality Assessment for Machine Learning @ Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD) (preprint arXiv:2010.13570)

[2020] "Proceeddings of the Workshop and Tutorial on "Interactive Adaptive Learning (IAL)", ECML PKDD 2020, Ghent D Kottke, G Krempl, V Lemaire, A Holzinger, A Calma,
[2020] « Learning active learning at the crossroads? evaluation and discussion », Louis Desreumaux, Vincent Lemaire, Workshop on "Interactive Adaptive Learning", ECML PKDD 2020
[2020] « Multivariate Time Series Classification: a relational way », Dominique Gay, Alexis Bondu, Vincent Lemaire, Marc Boullé, Fabrice Clérot in International Conference on Big Data Analytics and Knowledge Discovery (DAWAK 2020).
[2020] "Predictive K-means with local models" Vincent Lemaire, Oumaima Alaoui Ismaili, Antoine Cornuéjols, Dominique Gay In: Lu W., Zhu K.Q. (eds) Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2020. Lecture Notes in Computer Science, vol 12237. Springer, Cham. https://doi.org/10.1007/978-3-030-60470-7_10
[2020] "Sélections simultanées de variables et de représentations pour la classification de séries temporelles" Alexis Bondu, Dominique Gay, Vincent Lemaire, Marc Boullé, and Eole Cervenka, "Extraction et Gestion des Connaissance" 2020 (EGC)
[2020] "Apprentissage par renforcement de stratégies d’apprentissage actif : une évaluation" Louis Desreumaux, Vincent Lemaire, "Extraction et Gestion des Connaissance" 2020 (EGC)

[2019] "Proceeddings of the Workshop and Tutorial on "Interactive Adaptive Learning (IAL)", ECML PKDD 2019, Germany G Krempl, V Lemaire, D Kottke, A Calma, A Holzinger, R Polikar, B Sick
[2019] "FEARS: a FEature And Representation Selection approach for time series classification", Alexis Bondu, Dominique Gay, Vincent Lemaire, Marc Boullé, and Eole Cervenka, Asian Conference on Machine Learning (ACML 2019)
[2019] "Proactive Fiber Break Detection based on Quaternion Time Series and Automatic Variable Selection from Relational Data", Vincent Lemaire, Fabien Boitier, Jelena Pesic, Alexis Bondu, Stéphane Ragot and Fabrice Clérot, Workshop on Advanced Analytics and Learning on Temporal Data, European Conference on Machine Learning (ECML 2019),
[2019] "Toward a framework for seasonal time series forecasting using clustering", Colin Leverger, Simon Malinowski, Thomas Guyet, Vincent Lemaire, Alexis Bondu and Alexandre Termier - 20th International Conference on Intelligent Data Engineering and Automated Learning, The University of Manchester, November 2019
[2019] "Graph2Bots, Unsupervised Assistance for Designing Chatbots", Jean-Léon Bouraoui, Sonia Le Meitour, Romain Carbou, Lina M. Rojas-Barahona, Vincent Lemaire "Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL 2019)"
[2019] "Apprentissage fédératif pour la prédiction du churn : une évaluation" Sébastien Godard, Nicolas Voisine, Tanguy Urvoy, Vincent Lemaire, "Extraction et Gestion des Connaissance" 2019 (EGC)

[2018] "Proceeddings of the Workshop and Tutorial on "Interactive Adaptive Learning (IAL)", ECML PKDD 2018, Dublin, Ireland, G Krempl, V Lemaire, D Kottke, A Calma, A Holzinger, R Polikar, B Sick
[2018] "Day-ahead time series forecasting: application to capacity planning", C Leverger, V Lemaire, S Malinowski, T Guyet, L Rozé, Workshop on Advanced Analytics and Learning on Temporal Data, European Conference on Machine Learning (ECML)
[2018] "Should we Reload Time Series Classification Performance Evaluation ? (a position paper)", D Gay, V Lemaire, Workshop on Advanced Analytics and Learning on Temporal Data, European Conference on Machine Learning (ECML)
[2018] "TriClustering based outlier-shape score for time series in a fraud detection platform", P Lejeail, V Lemaire, A Cornuéjols, A Ouorou, Workshop on Advanced Analytics and Learning on Temporal Data, European Conference on Machine Learning (ECML)
[2018] "Seamless Optical Path Restoration with Just-in-Time Resource Allocation Leveraging Machine Learning", Fabien Boitier, Jelena Pesic, Vincent Lemaire, Eric Dutisseuil, Jose Manuel Estaran Tolosa, Philippe Jennevé, Nicolas Le Moing, Haïk Mardoyan and Patricia Layec, "European Conference on Optical Communication (ECOC), 2018
[2018] "Graph2Bots: Assistance automatisée à la conception d’agents dialoguants", Jean-Léon Bouraoui, Vincent Lemaire, "Extraction et Gestion des Connaissance", Atelier TextMine, 2018 (EGC)
[2018] "Apport des modèles locaux pour les K-moyennes prédictives", Vincent Lemaire, Oumaima Alaoui Ismaili, "Extraction et Gestion des Connaissance" 2018 (EGC)
[2018] "PerForecast : un outil d’automatisation de planning capacitaire et de prévision de l’évolution de séries temporelles univariées", Colin Leverger, Régis Marguerie, Vincent Lemaire, Thomas Guyet, Simon Malinowski, Démonstration à "Extraction et Gestion des Connaissance" 2018 (EGC)

[2017] "Cluster-Based Graphs for Conceiving Dialog Systems", Jean-Léon Bouraoui, Vincent Lemaire, Workshop DMNLP at European Conference on Machine Learning (ECML), 2017
[2017] Proceeddings of the Workshop and Tutorial on "Interactive Adaptive Learning (IAL)", ECML PKDD 2017, Skopje, Macedonia, Georg Krempl, Vincent Lemaire, Robi Polikar, Bernhard Sick, Daniel Kottke, Adrian Calma
[2017] "Neural Connectomics Challenge", Springer (book), D Battaglia, I Guyon, V Lemaire, J Orlandi, B Ray, J Soriano
[2017] "Proactive Fiber Damage Detection in Real-time Coherent", F. Boitier, V. Lemaire, J. Pesic, L . Chavarria, E. Dutisseuil, European Conference on Optical Communication (ECOC), 2017
[2017] "Learning Zoo", Vincent Lemaire, Christophe Salperwyck, Technical Report.
[2017] "The Data Mining Process : a (not so) short introduction", Vincent Lemaire, Marc Boullé, Fabrice Clérot, Nicolas Voisine, Carine Hue, Françoise Fessant, Romain Trinquart, This presentation is an brief introduction (a brief course) to data mining which is given in house in Orange Labs, 2017.
[2017] "Aide à l’automatisation de conception de systèmes de dialogue", Jean Leon Bouraoui, Vincent Lemaire, Atelier TextMine, in Extraction et Gestion des Connaissances (EGC), Grenoble, 2017.
[2017] "Un critère d’évaluation pour les K-moyennes prédictives" Oumaima Alaoui Ismaili, Vincent Lemaire, Antoine Cornuéjols, in Extraction et Gestion des Connaissances (EGC), Grenoble, 2017.

[2016] "Improving the Prediction Cost of Drift Handling Algorithms by Abstaining (ICDM), 2016" Pierre-Xavier Loeffel, Vincent Lemaire, Christophe Marsala, Marcin Detyniecki in International Conference on Data Mining (ICDM), 2016.
[2016] Proceedings of the Workshop on Active Learning: Applications, Foundations and Emerging Trends co-located with International Conference on Knowledge Technologies and Data-driven Business (i-KNOW 2016), Graz, Austria, October 18, 2016 Georg Krempl, Vincent Lemaire, Edwin Lughofer, Daniel Kottke
[2016] "Evaluation of predictive clustering quality", Oumaima Alaoui Ismaili, Vincent Lemaire, Antoine Cornuéjols, in Model-Based Clustering and Classification (MBC2), 2016.
[2016] "Analyse exploratoire par k-Coclustering avec Khiops CoViz (Demonstration EGC 2016)", Bruno Guerraz, Marc Boullé, Dominique Gay, Vincent Lemaire and Fabrice Clérot, in Conference 'Extraction et Gestion des Connaissances (EGC), Reims, 2016.
[2016] "Une méthode supervisée pour initialiser les centres des K-moyennes", Oumaima Alaoui Ismaili, Vincent Lemaire, Antoine Cornuéjols, in Extraction et Gestion des Connaissances (EGC), Reims, 2016
[2016] "Online learning of a weighted selective naive Bayes classifier with non-convex optimization", Carine Hue, Marc Boullé, Vincent Lemaire, Advances in Knowledge Discovery and Management (AKDM), 2015
[2016] "Lemaire et al - Un outil pour la classification a base de clustering pour decrire et predire simultanement (EGC 2016).pdf", Vincent Lemaire, Oumaima Alaoui Ismaili, Démo, Workshop CluCo, Extraction et Gestion des Connaissances (EGC), Reims, 2016

[2015] "How to Select Information That Matters - A Comparative Study on Active Learning Strategies for Classification", Christian Beyer, Georg Krempl, Vincent Lemaire, International conference on Knowledge Technologies and Data-Driven Business (i-KNOW), 2015 (best paper)
[2015] "Initialisation des k-moyennes à l’aide d’une décomposition supervisee des classes" Oumaima Alaoui Ismaili, Vincent Lemaire, Antoine Cornuéjols, Congrès de la Société Française de Classification (SFC)
[2015] "Increasing loyalty using predictive modeling in Business-to-Business Telecommunication", Patrick Luciano, Ismail Rebai, Vincent Lemaire, Workshop on ICT and Innovation Forecasting - From Theory to Practice & Applications") - a draft of the related paper
[2015] "Classification à base de clustering ou comment décrire et prédire simultanément", Oumaima Alaoui Ismaili, Vincent Lemaire, Antoine Cornuéjols in "Rencontres des Jeunes Chercheurs en Intelligence Artificielle (RJCIA)", Rennes, 2015
[2015] "Optimised Probabilistic Active Learning (OPAL) - For Fast, Non-Myopic, Cost-Sensitive Active Classification" Georg Krempl, Daniel Kottke, Vincent Lemaire Machine Learning ( best research paper 2015 of the Magdeburg University)
[2015] "Concept drift detection using supervised bivariate grids", Christophe Salperwyck, Marc Boullé, Vincent Lemaire in International Joint Conference on Neural Networks (IJCNN), IEEE, Ireland, 2015
[2015] "An Initialization Scheme for Supervized K-means" Vincent Lemaire, Oumaima Alaoui Ismaili, Antoine Cornuéjols, in International Joint Conference on Neural Networks (IJCNN), IEEE, Ireland, 2015
[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, Romain Trinquart, in Conference 'Extraction et Gestion des Connaissances (EGC), Luxembourg, 2015. (best industrial paper)
[2015] "Analyse exploratoire par k-Coclustering avec Khiops CoViz" Bruno Guerraz, Marc Boullé, Dominique Gay, Vincent Lemaire and Fabrice Clérot, in Atelier CluCo, Conference 'Extraction et Gestion des Connaissances (EGC), Luxembourg, 2015.
[2015] "A survey on supervised classification on data streams", Vincent Lemaire, Christophe Salperwyck, Alexis Bondu in a volume in the series Lecture Notes in Business Information Processing published by Springer which will be released in 2015
[2015] "Supervised pre-processings are useful for supervised clustering", Oumaima Alaoui Ismaili, Vincent Lemaire, Antoine Cornuejols, in the Springer Series “Studies in Classification, Data Analysis, and Knowledge Organization” which will be released in 2015
[2015] "First Connectomics Challenge: From Imaging to Connectivity", Javier G Orlandi, Bisakha Ray, Demian Battaglia Isabelle Guyon, Vincent Lemaire, Mehreen Saeed, Jordi Soriano, Alexander Statnikov, Olav Stetter, in JMLR: Workshop and Conference Proceedings
[2015] "Incremental Weighted Naive Bayes Classifiers for Data Streams", Christophe Salperwyck, Vincent Lemaire, Carine Hue, in the volume "Data Science, Learning by Latent Structures, and Knowledge Discovery" (2015, Chapter 17) of the Springer Series "Studies in Classification, Data Analysis, and Knowledge Organization"

[2014] "A supervised methodology to measure the variables contribution to a clustering", Oumaima Alaoui Ismaili, Vincent Lemaire, and Antoine Cornuéjols - in International Conference on Neural Information Processing (ICONIP), Kuching, Sarawak, Malaysia from 3 - 6 November 2014 (also best student poster at a french summer school)
[2014] ""Open Challenges for Data Stream Mining Research", Georg Krempl, Indre Zliobaite, Dariusz Brzezinski, Eyke Hüllermeier, Mark Last, Vincent Lemaire, Tino Noack, Ammar Shaker, Sonja Sievi, Myra Spiliopoulou, Jerzy Stefanowski - in SIGKDD Explorations (Special Issue on Big Data) (selected as notable article)
[2014] "K-means clustering on a classifier-induced representation space : application to customer contact personalization", in Annals of Information Systems, Springer - Special Issue on Real-World Data Mining Applications
[2014] "Design of the First Neuronal Connectomics Challenge: From Imaging to Connectivity", Isabelle Guyon, Demian Battaglia, Alice Guyon, Vincent Lemaire, Javier G. Orlandi, Mehreen Saeed, Jordi Soriano, Alexander Statnikov, Olav Stetter, Bisakha Ray in IEEE World Congress on Computational Intelligence (IEEE WCCI), Beijing, 2014.
[2014] "Apprentissage en ligne d’un Classifieur Bayésien naïf pondéré", Carine Hue, Marc Boullé and Vincent Lemaire. in Conference 'Extraction et Gestion des Connaissances (EGC), Rennes, 2014.
[2014] "Classifieur naïf de Bayes pondéré pour flux de données", Christophe Salperwyck, Vincent Lemaire and Carine Hue in Conference 'Extraction et Gestion des Connaissances (EGC), Rennes, 2014.
[2014] "Une méthode basée sur des effectifs pour calculer la contribution des variables à un clustering", Oumaima Alaoui Ismaili, Julien Salotti, Vincent Lemaire. in Atelier CluCo de la conférence Extraction et Gestion des Connaissances (EGC), Rennes, 2014.

[2013] " Real World Issues in Supervised Classification for data stream", Slides of a talk given at ECML 2013 - workshop RealStream, September 2013

[2013] "Incremental Decision Tree based on order statistics", C. Salperwyck & V. Lemaire in International Joint Conference on Neural Networks (IJCNN August 2013, Dallas) (and in the workshop AIL 2012 (Workshop on Active and Incremental Learning held at ECAI 2012, Montpellier) but this workshop has no proceedings)
[2013] "Design and Analysis of the Nomao challenge Active Learning in the Real-World", L. Candillier et V. Lemaire, in International Joint Conference on Neural Networks (IJCNN August 2013, Dallas) (and in the workshop ALRA (Workshop on Active Learning in Real world Application) held at ECML 2012, Bristol but this workshop has no proceedings)
[2013] "Grille bivariée pour la détection de changement dans un flux étiqueté" Christophe Salperwyck, Marc Boullé, Vincent Lemaire, in Conference 'Extraction et Gestion des Connaissances (EGC), Toulouse, 2013.
[2013] "A two layers incremental discretization based on order statistics", Christophe Salperwyck and Vincent Lemaire, in a volume by Springer in the series “Studies in Classification, Data Analysis, and Knowledge Organization (2013). (extended version after the Cladag 2011 presentation.

[2012] "A Complete Data Mining process to Manage the QoS of ADSL Services", F. Fessant & V. Lemaire in the workshop WAITS 2012 (Workshop on Artificial Intelligence for Telecommunications & Sensor Networks held at ECAI 2012, Montpellier)
[2012] "ICML-2011 Workshop on Unsupervised and Transfer learning", Isabelle Guyon, Daniel L. Silver, Gideon Dror, Graham Taylor and Vincent Lemaire, in JMLR:Workshop and Conference Proceedings 27 (2011)
[2012] "Arbres en ligne basés sur des statistiques d’ordre", Christophe Salperwyck, Vincent Lemaire, in the workshop "CIDN : Classification incrémentale et méthodes de détection de nouveauté" joint to the conference 'Extraction et Gestion des Connaissances (EGC), 2012.
[2012] "K-moyennes contraintes par un classifieur - Application à la personnalisation de scores de campagnes", Vincent Lemaire, Nicolas Creff, Fabrice Clérot , in 'Extraction et Gestion des Connaissances (EGC), 2012
[2012] "Analysis of the IJCNN 2011 UTL challenge", Isabelle Guyon, Gideon Dror, Vincent Lemaire, Daniel L. Silver, Graham Taylor, and David W. Aha, Special issue of the journal Neural Networks dedicated to 8% of the IJCNN 2011 papers

[2011] "A two layers incremental discretization based on order statistics", Christophe Salperwyck and Vincent Lemaire, in CLADAG (International metting of the CLAssification and Data Analysis Group of Italian Statistical Society), 2011,
[2011] "Learning with few examples: an empirical study on leading classifiers", Christophe Salperwyck and Vincent Lemaire, in International Joint Conference on Neural Networks (IJCNN), 2011)
[2011] "Unsupervised and TransferLearning Challenge", Isabelle Guyon, Gideon Dror, Vincent Lemaire, Graham Taylor and David Aha, in International Joint Conference on Neural Networks (IJCNN July 2011)
[2011] "Classification incrémentale supervisée : un panel introductif", Christophe Salperwyck and Vincent Lemaire, in a special number of the review 'Revue des Nouvelles Technologies de l'Information'
[2011] "Impact de la taille de l'ensemble d’apprentissage : une étude empirique", Christophe Salperwyck and Vincent Lemaire, in workshop "CIDN : Clustering incrémental et méthodes de détection de nouveauté" joint to the conference 'Extraction et Gestion des Connaissances (EGC), Brest, 2011
[2011] "Gestion de la QoS des services ADSL à l’aide d’un processus de data mining", Vincent Lemaire and Françoise Fessant, workshop "Data Mining, Applications, Use Cases and Success Stories" joint to the conference 'Extraction et Gestion des Connaissances (EGC), Brest, 2011.

[2010] "Post-hoc experiments for the active learning challenge", Christophe Salperwyck and Vincent Lemaire, in Technical report, Orange Labs, 2010, FT/RD/TECH/10/09/216.
[2010] "A method to build a representation using a classifier and its use in a K Nearest Neighbors-based deployment", Vincent Lemaire, Marc Boulle, Fabrice Clerot and Pascal Gouzien, in International Joint Conference on Neural Networks (IJCNN), 2010
[2010] "Results of the Active Learning Challenge", Isabelle Guyon, Gavin Cawley, Gideon Dror, Vincent Lemaire, in JMLR Workshop and Conference Proceedings and in the workshop 'Active Learning' of the 13th International Conference on Artificial Intelligence and Statistics (AISTATS) 2010)
[2010] "Exploration vs. exploitation in active learning: a Bayesian approach", Alexis Bondu, Vincent Lemaire and Marc Boulle, International Joint Conference on Neural Networks (IJCNN) - July 2010
[2010] "Design and Analysis of the WCCI 2010 Active Learning Challenge", Isabelle Guyon, Gavin Cawley, Gideon Dror and Vincent Lemaire, in International Joint Conference on Neural Networks (IJCNN) - July 2010
[2010] "Compromis exploration vs. exploitation en apprentissage actif : une approche Bayesienne", Alexis Bondu, Vincent Lemaire, Marc Boullé in 'Conference d'apprentissage (CAP)', Clermont Ferrand, May, 2010
[2010] "Une méthode pour construire une représentation à l'aide d'un classifieur et son utilisation dans un k-ppv", Vincent Lemaire, Marc Boullé, Pascal Gouzien, in 'Conference d'apprentissage (CAP)', Clermont Ferrand, May, 2010
[2010] "The Orange Customer Analysis Platform", Raphaël Féraud, Marc Boullé, Fabrice Clérot, Françoise Fessant, Vincent Lemaire, in Industrial Conference on Data Mining (ICDM), Berlin, July 2010.
[2010] "Une nouvelle stratégie d’Apprentissage Bayésienne", Alexis Bondu, Vincent Lemaire, Marc Boullé, in Extraction et Gestion des Connaissances (EGC), 2010.
[2010] Exhibition : "KAWAB : Un outil pour explorer les corrélations existantes dans un classifieur naïf de Bayes", Vincent Lemaire, in RFIA (Reconnaissance des Formes et Intelligence Artificielle), Caen, Fevrier 2010
[2010] "Correlation Analysis in Classifiers", Vincent Lemaire, Carine Hue, Olivier Bernier, in "Handbook of Research on Data Mining in Public and Private Sectors: Organizational and Government Applications"

[2009] "Analysis of the KDD Cup 2009: Fast Scoring on a Large Orange Customer Database", Isabelle Guyon, Vincent Lemaire, Marc Boullé, Gideon Dror, David Vogel, in JMLR Workshop and Conference Proceedings Volume 7: 1-22, 2009.
[2009] "Fast Scoring on a Large Database" [...]. the presentation of the KDD Cup 2009, and a technical report
[2009] "Design and analysis of the KDD cup 2009: fast scoring on a large orange customer database", ACM SIGKDD Explorations Newsletter archive, Volume 11 , Issue 2 (December 2009)
[2009] "Correlation Explorations in a Classification Model", Vincent Lemaire, Carine Hue, Olivier Bernier in the workshop Data Mining Case Studies and Practice Prize, SIGKDD 2009
[2009] "A Non-parametric Semi-supervised Discretization Method", Alexis Bondu, Marc Boullé, Vincent Lemaire, in Knowledge and Information Systems (KAIS) An International Journal
[2009] "Exploration des corrélations dans un classifieur, Application au placement d’offres commerciales", Vincent Lemaire, Carine Hue, in Extraction et Gestion des Connaissances (EGC), Strabourg.

[2008] "Data Mining : Exploration, Sélection, Compréhension", Vincent Lemaire, HABILITATION À DIRIGER DES RECHERCHES de l’Université Paris Sud (Orsay), spécialité Informatique
[2008] "A Non-parametric Semi-supervised Discretization Method", Alexis Bondu, Marc Boullé, Vincent Lemaire, in Proceedings of the International Conférence on Data Mining - December 2008
[2008] "A Multi-criterion Active Learning strategy: Application to Emotion Detection in Speech", A. Bondu and V. Lemaire, in Conférence Francophone sur l'apprentissage automatique (CAP) - May 2008
[2008] "Contact Personalization Using a Score Understanding Method", V. Lemaire, R. Féraud and N. Voisine, in International Joint Conference on Neural Networks (IJCNN), 2008
[2008] "Adaptive Curiosity for Emotions Detection in Speech", A. Bondu and V. Lemaire, in International Joint Conference on Neural Networks (IJCNN), 2008
[2008] "Réglage de la largeur d'une fenêtre de Parzen dans le cadre d'un apprentissage actif : une évaluation", V. Lemaire, A. Bondu and M. Chesnel, in Proceeding of 1st International Conference SIIE, 2008 Information Systems and Economic Intelligence
[2008] "Combining several SOM approaches in data mining: application to ADSL customer behaviours analysis", F. Fessant, V. Lemaire and F. Clérot, in the Springer series "Studies in Classification, Data Analysis, and Knowledge Organization"
[2008] "Etat de l'art sur les methodes statistiques d'apprentissage actif", A. Bondu, V. Lemaire, in the special number of the review 'Revue des Nouvelles Technologies de l'Information'

[2007] "Learning invariants to illumination changes typical of indoor environments: application to image color correction", B. Bascle, O. Bernier and V. Lemaire, International Journal of Imaging Systems and Technology (IJIST), special issue on "Applied Color Image Processing"
[2007] "Active Learning using Adaptive Curiosity", A. Bondu, V. Lemaire, in International Conference on Epigenetic Robotics: Modeling Cognitive Development in Robotic Systems, 2007,
[2007] "Purchase of data labels by batches: study of the impact on the planning of two active learning strategies", V. Lemaire, A. Bondu and F. Clérot, Technical Report
[2007] "Active Learning Strategies: a case study for detection of emotions in speech", A. Bondu, V. Lemaire and B. Poulain, in "Advances in Data Mining: Theoretical Aspects and Applications" P. Perner (Ed.), Industrial Conference on Data Mining 2007,
[2007] "Som based data mining approach to ADSL customer behavior analysis", F. Fessant, V. Lemaire and F. Clérot, invited paper at The 31st Annual Conference of the German Classification Society on Data Analysis, Machine Learning, and Applications, 2007
[2007] "Extraction d’information via une méthode d’interprétation de scores", V. Lemaire and R. Féraud, in Workshop 'Data mining dans la banque, l'assurance et la finance', workshop joint to the conference 'Extraction et Gestion des Connaissances (EGC), 2007
[2007] "Une méthode d'interprétation de scores", V. Lemaire and R. Féraud, in 'Extraction et Gestion des Connaissances (EGC)',2007
[2007] "Apprentissage actif d’émotions dans les dialogues Homme-Machine", A. Bondu, V. Lemaire and B. Poulain, in Extraction et Gestion des Connaissances (EGC)", 2007

[2006] "Driven Forward Features Selection: a comparative study on Neural Networks", V. Lemaire and R. Féraud, in Int. Conf. on Neural Information Processsing (ICONIP), 2006
[2006] "A statistical approach for learning invariants: application to image color correction and learning invariants to illumination", B. Bascle, O. Bernier and V. Lemaire, in Int. Conf. on Neural Information Processsing (ICONIP)2006
[2006] Illumination-invariant Color Correction", B. Bascle, O. Bernier and V. Lemaire, invited paper at the International Workshop on Intelligent Computing in Pattern Analysis/Synthesis (IWICPAS), China.
[2006] "Looking for a relevant similarity criterion for HRTF clustering: a comparative study", V. Lemaire - R. Nicol, S. Busson and A. Bondu, in Audio Engineering Society Convention, 2006
[2006] "Effective Organization and Visualization of Web Search Results", * N. Bonnel, V. Lemaire, A. Cotarmanac’h and A. Morin, in Internet and Multimedia Systems and Applications (Euro IMSA), 2006
[2006] "Modélisation de HRTF par réseaux de neurones - Classification : Métrologie et traitement du signal", S. Busson, R. Nicol, V. Choqueuse, P. Vovor, V. Lemaire, F. Clérot, in Congrès de la société française d'acoustique (CFA), 2006
[2006] Book : "Feature extraction, foundations and applications", Chapter "An Input Variable Importance Definition based on Empirical Data Probability" V. Lemaire and F. Clérot

[2005] "Individualized HRTFs From Few Measurements: a Statistical Learning Approach", V. Lemaire, F. Clerot, S. Busson, R. Nicol and V. Choqueuse, in International Joint Conference on Neural Networks (IJCNN), 2005
[2005] Book : "Classification and Clustering for Knowledge Discover", Series: Studies in Computational Intelligence, Vol. 4, Editeurs : Halgamuge, Saman K.; Wang, Lipo (Eds.), Approx. 300 p., Hardcover, ISBN: 3-540-26073-0, Chapter : " The many faces of Kohonen Map". V. Lemaire and F. Clérot

[2004] "An Input Variable Importance Definition based on Empirical Data Probability and Its Use en Variable Selection", V. Lemaire and F. Clérot, in International Joint Conference on Neural Networks (IJCNN), 2004

[2002] "SOM-based clustering for on-line fraud behaviour classification : a case study", V.Lemaire and F. Clérot, in Fuzzy Systems and Knowledge Discovery (FSKD), 2002.
[2002] Bagging Using the VMSE Cost Function, V. Lemaire, IDIAP-RR 02-27.

My PhD publications

[PhD] "Une nouvelle fonction de coût régularisante dans les réseaux de neurones artificiels : Application à l'estimation des temps de blocage dans un noeud ATM", V. Lemaire, Thèse de doctorat présentée : devant l'université de Paris 6 pour obtenir le grade de : DOCTEUR DE L'UNIVERSITÉ DE PARIS 6 (Spécialité : Informatique). Septembre 1999
[PhD] Une nouvelle fonction de coût régularisante dans les réseaux de neurones artificiels. Application aux réseaux discriminants", V. Lemaire, in Revue d'Intelligence Artificielle, 1999.
[PhD] Une nouvelle fonction de coût régularisante dans les réseaux de neurones artificiels : Application à la classification", V. Lemaire, O. Bernier, D. Collobert and F. Clérot. in Première Conférence d'Apprentissage Paris, 14 au 18 juin 1999 (CAP99)
[PhD] "A new method to increase the margin of multilayer perceptrons" , V. Lemaire, O. Bernier, F. Clérot and D. Collobert, in Neural Processing Letter, 1999
[PhD] "Estimation of the blocking probabilities in a ATM Network node using Artificial Neural Networks for Connection Admission", V. Lemaire, F. Clérot. in Control International Teletraffic Congress (ITC16), Scotland, Edinburgh, june 1999.
[PhD] "MULTRAK: a system for Automatic Multiperson Localization and tracking in real-Time", O. Bernier, M. Collobert, R. Feraud, V. Lemaire, J.-E Viallet, D. Collobert, in International Conference on Image Processing (ICIP), 1998.
[PhD] "Un système de localisation et de suivi de personnes pour visioconférences", M. Collobert, O. Bernier, R. Feraud, V. Lemaire, J.-E Viallet, D. Collobert, in CORESA'98, 1998.
[PhD] "Connection Admission Control in ATM network using an artificial Neural Network", V. Lemaire, in Helnet97 International Workshop On Neural Network (ICANN) Montreux, Suisse, october 1997

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