Vincent Lemaire

ORCID

Publication Activity (10 Years)

Years Active: 1998-2024
Publications (10 Years): 66

Top Venues

Publications

Aurélien Renault, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire
Early Classification of Time Series: Taxonomy and Benchmark. CoRR (2024)
Colin Troisemaine, Vincent Lemaire
Constructing Variables Using Classifiers as an Aid to Regression: An Empirical Assessment. CoRR (2024)
Arthur Hoarau, Vincent Lemaire, Yolande Le Gall, Jean-Christophe Dubois, Arnaud Martin
Evidential uncertainty sampling strategies for active learning. Mach. Learn. 113 (9) (2024)
Colin Troisemaine, Alexandre Reiffers-Masson, Stéphane Gosselin, Vincent Lemaire, Sandrine Vaton
A practical approach to novel class discovery in tabular data. Data Min. Knowl. Discov. 38 (4) (2024)
Colin Troisemaine, Joachim Flocon-Cholet, Stéphane Gosselin, Alexandre Reiffers-Masson, Sandrine Vaton, Vincent Lemaire
An Interactive Interface for Novel Class Discovery in Tabular Data. CoRR (2023)
Aurélien Renault, Alexis Bondu, Vincent Lemaire, Dominique Gay
Automatic Feature Engineering for Time Series Classification: Evaluation and Discussion. IJCNN (2023)
Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols
Biquality Learning: a Framework to Design Algorithms Dealing with Closed-Set Distribution Shifts. CoRR (2023)
Vincent Lemaire, Nathan Le Boudec, Françoise Fessant, Victor Guyomard
Viewing the process of generating counterfactuals as a source of knowledge - Application to the Naive Bayes classifier. CoRR (2023)
Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols
Biquality learning: a framework to design algorithms dealing with closed-set distribution shifts. Mach. Learn. 112 (12) (2023)
Vincent Lemaire, Fabrice Clérot, Marc Boullé
An Efficient Shapley Value Computation for the Naive Bayes Classifier. CoRR (2023)
Arik Ermshaus, Patrick Schäfer, Anthony J. Bagnall, Thomas Guyet, Georgiana Ifrim, Vincent Lemaire, Ulf Leser, Colin Leverger, Simon Malinowski
Human Activity Segmentation Challenge @ ECML/PKDD'23. AALTD@ECML/PKDD (2023)
Colin Troisemaine, Joachim Flocon-Cholet, Stéphane Gosselin, Alexandre Reiffers-Masson, Sandrine Vaton, Vincent Lemaire
An Interactive Interface for Novel Class Discovery in Tabular Data. ECML/PKDD (7) (2023)
Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols
biquality-learn: a Python library for Biquality Learning. CoRR (2023)
Arthur Hoarau, Vincent Lemaire, Arnaud Martin, Jean-Christophe Dubois, Yolande Le Gall
Evidential uncertainties on rich labels for active learning. CoRR (2023)
Vincent Lemaire, Fabrice Clérot, Marc Boullé
Comparaison des valeurs de Shapley et des valeurs du poids de l'évidence dans le cas du classifieur naïf de Bayes. EGC (2023)
Colin Troisemaine, Joachim Flocon-Cholet, Stéphane Gosselin, Sandrine Vaton, Alexandre Reiffers-Masson, Vincent Lemaire
Découvrir de nouvelles classes dans des données tabulaires. EGC (2023)
Colin Troisemaine, Alexandre Reiffers-Masson, Stéphane Gosselin, Vincent Lemaire, Sandrine Vaton
A Practical Approach to Novel Class Discovery in Tabular Data. CoRR (2023)
Aurélien Renault, Alexis Bondu, Vincent Lemaire, Dominique Gay
Automatic Feature Engineering for Time Series Classification: Evaluation and Discussion. CoRR (2023)
Colin Troisemaine, Vincent Lemaire, Stéphane Gosselin, Alexandre Reiffers-Masson, Joachim Flocon-Cholet, Sandrine Vaton
Novel Class Discovery: an Introduction and Key Concepts. CoRR (2023)
Colin Troisemaine, Joachim Flocon-Cholet, Stéphane Gosselin, Sandrine Vaton, Alexandre Reiffers-Masson, Vincent Lemaire
A Method for Discovering Novel Classes in Tabular Data. ICKG (2022)
Colin Troisemaine, Joachim Flocon-Cholet, Stéphane Gosselin, Sandrine Vaton, Alexandre Reiffers-Masson, Vincent Lemaire
Découvrir de nouvelles classes dans des données tabulaires. CoRR (2022)
Colin Troisemaine, Vincent Lemaire
Construction de variables à l'aide de classifieurs comme aide à la régression : une évaluation empirique. EGC (2022)
Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire
ECOTS: Early Classification in Open Time Series. CoRR (2022)
Alexis Bondu, Youssef Achenchabe, Albert Bifet, Fabrice Clérot, Antoine Cornuéjols, João Gama, Georges Hébrail, Vincent Lemaire, Pierre-Francois Marteau
Open challenges for Machine Learning based Early Decision-Making research. SIGKDD Explor. 24 (2) (2022)
Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire
Early and Revocable Time Series Classification. IJCNN (2022)
Alexis Bondu, Youssef Achenchabe, Albert Bifet, Fabrice Clérot, Antoine Cornuéjols, João Gama, Georges Hébrail, Vincent Lemaire, Pierre-François Marteau
Open challenges for Machine Learning based Early Decision-Making research. CoRR (2022)
Colin Troisemaine, Joachim Flocon-Cholet, Stéphane Gosselin, Sandrine Vaton, Alexandre Reiffers-Masson, Vincent Lemaire
A Method for Discovering Novel Classes in Tabular Data. CoRR (2022)
Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols
Repondération Préférentielle pour l'Apprentissage Biqualité. EGC (2022)
Laura Uhl, Vincent Augusto, Vincent Lemaire, Youenn Alexandre, Fanny Jardinaud, Paolo Bercelli, Saber Aloui
Progressive prediction of hospitalisation and patient disposition in the emergency department. Big Data (2022)
Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire
When to Classify Events in Open Times Series? ACML (2022)
Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols
Contrastive Representations for Label Noise Require Fine-Tuning. IAL@PKDD/ECML (2021)
Paul-Emile Zafar, Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire
Early Classification of Time Series: Cost-based multiclass Algorithms. DSAA (2021)
Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire
Early and Revocable Time Series Classification. CoRR (2021)
Xihui Wang, Pascale Kuntz, Frank Meyer, Vincent Lemaire
Multi-Label kNN classifier with Online Dual Memory on data stream. ICDM (Workshops) (2021)
Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols
Contrastive Representations for Label Noise Require Fine-Tuning. CoRR (2021)
Dominique Gay, Alexis Bondu, Vincent Lemaire, Marc Boullé
Interpretable Feature Construction for Time Series Extrinsic Regression. CoRR (2021)
Colin Troisemaine, Vincent Lemaire
Construction de variables à l'aide de classifieurs comme aide à la régression. CoRR (2021)
Dominique Gay, Alexis Bondu, Vincent Lemaire, Marc Boullé
Interpretable Feature Construction for Time Series Extrinsic Regression. PAKDD (1) (2021)
Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire
Early Classification of Time Series is Meaningful. CoRR (2021)
Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols, Adam Ouorou
Importance Reweighting for Biquality Learning. IJCNN (2021)
Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols, Adam Ouorou
From Weakly Supervised Learning to Biquality Learning: an Introduction. IJCNN (2021)
Daniel Zhu, Arnaud Martin, Yolande Le Gall, Jean-Christophe Dubois, Vincent Lemaire
Evidential Nearest Neighbours in Active Learning. IAL@PKDD/ECML (2021)
Dominique Gay, Alexis Bondu, Vincent Lemaire, Marc Boullé, Fabrice Clérot
Multivariate Time Series Classification: A Relational Way. DaWaK (2020)
Vincent Lemaire, Oumaima Alaoui Ismaili, Antoine Cornuéjols, Dominique Gay
Predictive K-means with local models. CoRR (2020)
Hugo Le Baher, Vincent Lemaire, Romain Trinquart
On the intrinsic robustness of some leading classifiers and symetric loss function - an empirical evaluation. CoRR (2020)
Louis Desreumaux, Vincent Lemaire
Apprentissage par renforcement de stratégies d'apprentissage actif : une évaluation. EGC (2020)
Alexis Bondu, Dominique Gay, Vincent Lemaire, Marc Boullé, Eole Cervenka
Sélections simultanées de variables et de représentations pour la classification de séries temporelles. EGC (2020)
Louis Desreumaux, Vincent Lemaire
Learning Active Learning at the Crossroads? Evaluation and Discussion. IAL@PKDD/ECML (2020)
Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols
Importance Reweighting for Biquality Learning. CoRR (2020)
Louis Desreumaux, Vincent Lemaire
Learning active learning at the crossroads? evaluation and discussion. CoRR (2020)
Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols, Adam Ouorou
From Weakly Supervised Learning to Biquality Learning, a brief introduction. CoRR (2020)
Jean Léon Bouraoui, Sonia Le Meitour, Romain Carbou, Lina Maria Rojas-Barahona, Vincent Lemaire
Graph2Bots, Unsupervised Assistance for Designing Chatbots. SIGdial (2019)
Dominique Gay, Vincent Lemaire
Should we Reload Time Series Classification Performance Evaluation ? (a position paper). CoRR (2019)
Vincent Lemaire, Fabien Boitier, Jelena Pesic, Alexis Bondu, Stéphane Ragot, Fabrice Clérot
Proactive Fiber Break Detection Based on Quaternion Time Series and Automatic Variable Selection from Relational Data. AALTD@PKDD/ECML (2019)
Sébastien Godard, Nicolas Voisine, Tanguy Urvoy, Vincent Lemaire
Apprentissage fédératif pour la prédiction du churn : une évaluation. EGC (2019)
Alexis Bondu, Dominique Gay, Vincent Lemaire, Marc Boullé, Eole Cervenka
FEARS: a Feature and Representation Selection approach for Time Series Classification. ACML (2019)
Colin Leverger, Simon Malinowski, Thomas Guyet, Vincent Lemaire, Alexis Bondu, Alexandre Termier
Toward a Framework for Seasonal Time Series Forecasting Using Clustering. IDEAL (1) (2019)
Fabien Boitier, Jelena Pesic, Vincent Lemaire, Eric Dutisseuil, Jose Manuel Estaran Tolosa, Philippe Jenneve, Nicolas Le Moing, Haïk Mardoyan, Patricia Layec
Seamless Optical Path Restoration with Just-in-Time Resource Allocation Leveraging Machine Learning. ECOC (2018)
Colin Leverger, Vincent Lemaire, Simon Malinowski, Thomas Guyet, Laurence Rozé
Day-ahead time series forecasting: application to capacity planning. CoRR (2018)
Colin Leverger, Régis Marguerie, Vincent Lemaire, Thomas Guyet, Simon Malinowski
PerForecast : un outil de prévision de l'évolution de séries temporelles pour le planning capacitaire. EGC (2018)
Vincent Lemaire, Oumaima Alaoui Ismaili
Apport des modèles locaux pour les K-moyennes prédictives. EGC (2018)
Oumaima Alaoui Ismaili, Vincent Lemaire, Antoine Cornuéjols
Un critère d'évaluation pour les K-moyennes prédictives. EGC (2017)
Fabien Boitier, Vincent Lemaire, Jelena Pesic, Lucia Chavarría, Patricia Layec, Sébastien Bigo, Eric Dutisseuil
Proactive Fiber Damage Detection in Real-time Coherent Receiver. ECOC (2017)
Pierre-Xavier Loeffel, Vincent Lemaire, Christophe Marsala, Marcin Detyniecki
Improving the Prediction Cost of Drift Handling Algorithms by Abstaining. ICDM Workshops (2016)
Bruno Guerraz, Marc Boullé, Dominique Gay, Vincent Lemaire, Fabrice Clérot
Analyse exploratoire par k-Coclustering avec Khiops CoViz. EGC (2016)
Oumaima Alaoui Ismaili, Vincent Lemaire, Antoine Cornuéjols
Une méthode supervisée pour initialiser les centres des K-moyennes. EGC (2016)
Georg Krempl, Daniel Kottke, Vincent Lemaire
Optimised probabilistic active learning (OPAL) - For fast, non-myopic, cost-sensitive active classification. Mach. Learn. 100 (2-3) (2015)
Vincent Lemaire, Oumaima Alaoui Ismaili, Antoine Cornuéjols
An initialization scheme for supervized K-means. IJCNN (2015)
Patrick Luciano, Ismail Rebai, Vincent Lemaire
Increasing loyalty using predictive modeling in Business-to-Business Telecommunication. CoRR (2015)
Carine Hue, Marc Boullé, Vincent Lemaire
Online Learning of a Weighted Selective Naive Bayes Classifier with Non-convex Optimization. EGC (best of volume) (2015)
Christian Beyer, Georg Krempl, Vincent Lemaire
How to select information that matters: a comparative study on active learning strategies for classification. I-KNOW (2015)
Christophe Salperwyck, Marc Boullé, Vincent Lemaire
Concept drift detection using supervised bivariate grids. IJCNN (2015)
Cedric Thao, Nicolas Voisine, Vincent Lemaire, Romain Trinquart
Feedback - Study and Improvement of the Random Forest of the Mahout library in the context of marketing data of Orange. EGC (2015)
Vincent Lemaire, Christophe Salperwyck, Alexis Bondu
A Survey on Supervised Classification on Data Streams. eBISS (2014)
Georg Krempl, Indre Zliobaite, Dariusz Brzezinski, Eyke Hüllermeier, Mark Last, Vincent Lemaire, Tino Noack, Ammar Shaker, Sonja Sievi, Myra Spiliopoulou, Jerzy Stefanowski
Open challenges for data stream mining research. SIGKDD Explor. 16 (1) (2014)
Oumaima Alaoui Ismaili, Vincent Lemaire, Antoine Cornuéjols
Supervised Pre-processings Are Useful for Supervised Clustering. ECDA (2014)
Oumaima Alaoui Ismaili, Vincent Lemaire, Antoine Cornuéjols
A Supervised Methodology to Measure the Variables Contribution to a Clustering. ICONIP (1) (2014)
Christophe Salperwyck, Vincent Lemaire, Carine Hue
Classifieur naïf de Bayes pondéré pour flux de données. EGC (2014)
Carine Hue, Marc Boullé, Vincent Lemaire
Apprentissage incrémental anytime d'un classifieur Bayésien naïf pondéré. EGC (2014)
Javier G. Orlandi, Bisakha Ray, Demian Battaglia, Isabelle Guyon, Vincent Lemaire, Mehreen Saeed, Alexander R. Statnikov, Olav Stetter, Jordi Soriano
First Connectomics Challenge: From Imaging to Connectivity. Neural Connectomics (2014)
Isabelle Guyon, Demian Battaglia, Alice Guyon, Vincent Lemaire, Javier G. Orlandi, Bisakha Ray, Mehreen Saeed, Jordi Soriano, Alexander R. Statnikov, Olav Stetter
Design of the first neuronal connectomics challenge: From imaging to connectivity. IJCNN (2014)
Christophe Salperwyck, Marc Boullé, Vincent Lemaire
Grille bivariée pour la détection de changement dans un flux étiqueté. EGC (2013)
Laurent Candillier, Vincent Lemaire
Active learning in the real-world design and analysis of the Nomao challenge. IJCNN (2013)
Christophe Salperwyck, Vincent Lemaire, Carine Hue
Incremental Weighted Naive Bays Classifiers for Data Stream. ECDA (2013)
Christophe Salperwyck, Vincent Lemaire
Incremental decision tree based on order statistics. IJCNN (2013)
Vincent Lemaire, Nicolas Creff, Fabrice Clérot
K-moyennes contraintes par un classifieur. Application à la personnalisation de scores de campagnes. EGC (2012)
Isabelle Guyon, Gideon Dror, Vincent Lemaire, Daniel L. Silver, Graham W. Taylor, David W. Aha
Analysis of the IJCNN 2011 UTL challenge. Neural Networks 32 (2012)
Daniel L. Silver, Isabelle Guyon, Graham W. Taylor, Gideon Dror, Vincent Lemaire
ICML2011 Unsupervised and Transfer Learning Workshop. ICML Unsupervised and Transfer Learning (2012)
Christophe Salperwyck, Vincent Lemaire
Learning with few examples: An empirical study on leading classifiers. IJCNN (2011)
Isabelle Guyon, Gideon Dror, Vincent Lemaire, Graham W. Taylor, David W. Aha
Unsupervised and transfer learning challenge. IJCNN (2011)
Isabelle Guyon, Gavin C. Cawley, Gideon Dror, Vincent Lemaire
Results of the Active Learning Challenge. Active Learning and Experimental Design @ AISTATS (2011)
Alexis Bondu, Vincent Lemaire, Marc Boullé
Une nouvelle stratégie d'apprentissage Bayésienne. EGC (2010)
Alexis Bondu, Marc Boullé, Vincent Lemaire
A non-parametric semi-supervised discretization method. Knowl. Inf. Syst. 24 (1) (2010)
Christophe Salperwyck, Vincent Lemaire
Classification incrémentale supervisée : un panel introductif. AAFD (2010)
Alexis Bondu, Vincent Lemaire, Marc Boullé
Exploration vs. exploitation in active learning : A Bayesian approach. IJCNN (2010)
Raphaël Féraud, Marc Boullé, Fabrice Clérot, Françoise Fessant, Vincent Lemaire
The Orange Customer Analysis Platform. ICDM (2010)
Isabelle Guyon, Gavin C. Cawley, Gideon Dror, Vincent Lemaire
Design and analysis of the WCCI 2010 active learning challenge. IJCNN (2010)
Vincent Lemaire, Marc Boullé, Fabrice Clérot, Pascal Gouzien
A method to build a representation using a classifier and its use in a K Nearest Neighbors-based deployment. IJCNN (2010)
Isabelle Guyon, Vincent Lemaire, Marc Boullé, Gideon Dror, David Vogel
Design and analysis of the KDD cup 2009: fast scoring on a large orange customer database. SIGKDD Explor. 11 (2) (2009)
Vincent Lemaire, Carine Hue
Exploration des corrélations dans un classifieur - Application au placement d'offres commerciales. EGC (2009)

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Publication Activity (10 Years)

Top Topics

Top Venues

Vincent Lemaire