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ORCIDVincent Lemaire 0001
Person information
- affiliation: Orange Labs, Lannion, France
Other persons with the same name
- Vincent Lemaire 0002
![[0000-0002-0433-7722]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-0433-7722")
— Sorbonne University, LPSM, Paris, France - Vincent Lemaire 0003 — National Institute for Industrial Environment and Risks, Verneuil-en-Halatte, France
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2020 – today
- 2024
[j11]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): 2087-2116 (2024)- [j10]Arthur Hoarau, Vincent Lemaire, Yolande Le Gall, Jean-Christophe Dubois, Arnaud Martin:
Evidential uncertainty sampling strategies for active learning. Mach. Learn. 113(9): 6453-6474 (2024) - [i28]Colin Troisemaine, Vincent Lemaire:
Constructing Variables Using Classifiers as an Aid to Regression: An Empirical Assessment. CoRR abs/2403.06829 (2024) - [i27]Aurélien Renault, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire:
Early Classification of Time Series: Taxonomy and Benchmark. CoRR abs/2406.18332 (2024) - 2023
- [j9]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): 4663-4692 (2023) - [c78]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: 3-13 - [c77]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: 385-392 - [c76]Colin Troisemaine, Joachim Flocon-Cholet, Stéphane Gosselin, Sandrine Vaton, Alexandre Reiffers-Masson, Vincent Lemaire:
Découvrir de nouvelles classes dans des données tabulaires. EGC 2023: 467-474 - [c75]Aurélien Renault, Alexis Bondu, Vincent Lemaire, Dominique Gay:
Automatic Feature Engineering for Time Series Classification: Evaluation and Discussion. IJCNN 2023: 1-10 - [c74]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: 295-299 - [e15]Thomas Guyet, Georgiana Ifrim, Simon Malinowski, Anthony J. Bagnall, Patrick Schäfer, Vincent Lemaire:
Advanced Analytics and Learning on Temporal Data - 7th ECML PKDD Workshop, AALTD 2022, Grenoble, France, September 19-23, 2022, Revised Selected Papers. Lecture Notes in Computer Science 13812, Springer 2023, ISBN 978-3-031-24377-6 [contents] - [e14]Georgiana Ifrim, Romain Tavenard, Anthony J. Bagnall, Patrick Schäfer, Simon Malinowski, Thomas Guyet, Vincent Lemaire:
Advanced Analytics and Learning on Temporal Data - 8th ECML PKDD Workshop, AALTD 2023, Turin, Italy, September 18-22, 2023, Revised Selected Papers. Lecture Notes in Computer Science 14343, Springer 2023, ISBN 978-3-031-49895-4 [contents] - [e13]Mirko Bunse, Barbara Hammer, Georg Krempl, Vincent Lemaire, Alaa Tharwat, Amal Saadallah:
Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2023), Torino, Italy, September 22nd, 2023. CEUR Workshop Proceedings 3470, CEUR-WS.org 2023 [contents] - [i26]Colin Troisemaine, Vincent Lemaire, Stéphane Gosselin, Alexandre Reiffers-Masson, Joachim Flocon-Cholet, Sandrine Vaton:
Novel Class Discovery: an Introduction and Key Concepts. CoRR abs/2302.12028 (2023) - [i25]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 abs/2306.12919 (2023) - [i24]Vincent Lemaire, Fabrice Clérot, Marc Boullé:
An Efficient Shapley Value Computation for the Naive Bayes Classifier. CoRR abs/2307.16718 (2023) - [i23]Aurélien Renault, Alexis Bondu, Vincent Lemaire, Dominique Gay:
Automatic Feature Engineering for Time Series Classification: Evaluation and Discussion. CoRR abs/2308.01071 (2023) - [i22]Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols:
biquality-learn: a Python library for Biquality Learning. CoRR abs/2308.09643 (2023) - [i21]Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols:
Biquality Learning: a Framework to Design Algorithms Dealing with Closed-Set Distribution Shifts. CoRR abs/2308.15132 (2023) - [i20]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 abs/2309.04284 (2023) - [i19]Arthur Hoarau, Vincent Lemaire, Arnaud Martin, Jean-Christophe Dubois, Yolande Le Gall:
Evidential uncertainties on rich labels for active learning. CoRR abs/2309.12494 (2023) - [i18]Colin Troisemaine, Alexandre Reiffers-Masson, Stéphane Gosselin, Vincent Lemaire, Sandrine Vaton:
A Practical Approach to Novel Class Discovery in Tabular Data. CoRR abs/2311.05440 (2023) - 2022
- [j8]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): 12-31 (2022) - [c73]Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire:
When to Classify Events in Open Times Series? ACML 2022: 1-16 - [c72]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. IEEE Big Data 2022: 1719-1728 - [c71]Colin Troisemaine, Vincent Lemaire:
Construction de variables à l'aide de classifieurs comme aide à la régression : une évaluation empirique. EGC 2022: 217-224 - [c70]Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols:
Repondération Préférentielle pour l'Apprentissage Biqualité. EGC 2022: 339-346 - [c69]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: 265-274 - [c68]Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire:
Early and Revocable Time Series Classification. IJCNN 2022: 1-8 - [e12]Georg Krempl, Vincent Lemaire, Daniel Kottke, Andreas Holzinger, Barbara Hammer:
Proceedings of the Workshop on Interactive Adaptive Learning (IAL 2021) co-located with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2021), Bilbao, Spain, September 13, 2021. CEUR Workshop Proceedings 3079, CEUR-WS.org 2022 [contents] - [i17]Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire:
ECOTS: Early Classification in Open Time Series. CoRR abs/2204.00392 (2022) - [i16]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 abs/2204.13111 (2022) - [i15]Colin Troisemaine, Joachim Flocon-Cholet, Stéphane Gosselin, Sandrine Vaton, Alexandre Reiffers-Masson, Vincent Lemaire:
A Method for Discovering Novel Classes in Tabular Data. CoRR abs/2209.01217 (2022) - [i14]Colin Troisemaine, Joachim Flocon-Cholet, Stéphane Gosselin, Sandrine Vaton, Alexandre Reiffers-Masson, Vincent Lemaire:
Découvrir de nouvelles classes dans des données tabulaires. CoRR abs/2211.16352 (2022) - 2021
- [c67]Paul-Emile Zafar, Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire:
Early Classification of Time Series: Cost-based multiclass Algorithms. DSAA 2021: 1-10 - [c66]Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols, Adam Ouorou:
Importance Reweighting for Biquality Learning. IJCNN 2021: 1-8 - [c65]Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols, Adam Ouorou:
From Weakly Supervised Learning to Biquality Learning: an Introduction. IJCNN 2021: 1-10 - [c64]Xihui Wang, Pascale Kuntz, Frank Meyer, Vincent Lemaire:
Multi-Label kNN classifier with Online Dual Memory on data stream. ICDM (Workshops) 2021: 405-413 - [c63]Dominique Gay, Alexis Bondu, Vincent Lemaire, Marc Boullé:
Interpretable Feature Construction for Time Series Extrinsic Regression. PAKDD (1) 2021: 804-816 - [c62]Daniel Zhu, Arnaud Martin, Yolande Le Gall, Jean-Christophe Dubois, Vincent Lemaire:
Evidential Nearest Neighbours in Active Learning. IAL@PKDD/ECML 2021: 35-49 - [c61]Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols:
Contrastive Representations for Label Noise Require Fine-Tuning. IAL@PKDD/ECML 2021: 89-104 - [e11]Vincent Lemaire, Simon Malinowski, Anthony J. Bagnall, Thomas Guyet, Romain Tavenard, Georgiana Ifrim:
Advanced Analytics and Learning on Temporal Data - 6th ECML PKDD Workshop, AALTD 2021, Bilbao, Spain, September 13, 2021, Revised Selected Papers. Lecture Notes in Computer Science 13114, Springer 2021, ISBN 978-3-030-91444-8 [contents] - [e10]Jérôme Azé, Vincent Lemaire:
Extraction et Gestion des Connaissances, EGC 2021, 25-29 Janvier 2021, Montpellier, France. RNTI E-37, Éditions RNTI 2021, ISBN 979-10-96289-14-1 [contents] - [i13]Dominique Gay, Alexis Bondu, Vincent Lemaire, Marc Boullé:
Interpretable Feature Construction for Time Series Extrinsic Regression. CoRR abs/2103.10247 (2021) - [i12]Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire:
Early Classification of Time Series is Meaningful. CoRR abs/2104.13257 (2021) - [i11]Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols:
Contrastive Representations for Label Noise Require Fine-Tuning. CoRR abs/2108.09154 (2021) - [i10]Youssef Achenchabe, Alexis Bondu, Antoine Cornuéjols, Vincent Lemaire:
Early and Revocable Time Series Classification. CoRR abs/2109.10285 (2021) - [i9]Colin Troisemaine, Vincent Lemaire:
Construction de variables à l'aide de classifieurs comme aide à la régression. CoRR abs/2112.03703 (2021) - 2020
- [c60]Dominique Gay, Alexis Bondu, Vincent Lemaire, Marc Boullé, Fabrice Clérot:
Multivariate Time Series Classification: A Relational Way. DaWaK 2020: 316-330 - [c59]Louis Desreumaux, Vincent Lemaire:
Apprentissage par renforcement de stratégies d'apprentissage actif : une évaluation. EGC 2020: 237-244 - [c58]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: 415-424 - [c57]Louis Desreumaux, Vincent Lemaire:
Learning Active Learning at the Crossroads? Evaluation and Discussion. IAL@PKDD/ECML 2020: 38-54 - [e9]Daniel Kottke, Georg Krempl, Vincent Lemaire, Andreas Holzinger, Adrian Calma:
Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2020), Ghent, Belgium, September 14th, 2020. CEUR Workshop Proceedings 2660, CEUR-WS.org 2020 [contents] - [e8]Vincent Lemaire, Simon Malinowski, Anthony J. Bagnall, Alexis Bondu, Thomas Guyet, Romain Tavenard:
Advanced Analytics and Learning on Temporal Data - 4th ECML PKDD Workshop, AALTD 2019, Würzburg, Germany, September 20, 2019, Revised Selected Papers. Lecture Notes in Computer Science 11986, Springer 2020, ISBN 978-3-030-39097-6 [contents] - [e7]Vincent Lemaire, Simon Malinowski, Anthony J. Bagnall, Thomas Guyet, Romain Tavenard, Georgiana Ifrim:
Advanced Analytics and Learning on Temporal Data - 5th ECML PKDD Workshop, AALTD 2020, Ghent, Belgium, September 18, 2020, Revised Selected Papers. Lecture Notes in Computer Science 12588, Springer 2020, ISBN 978-3-030-65741-3 [contents] - [i8]Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols:
Importance Reweighting for Biquality Learning. CoRR abs/2010.09621 (2020) - [i7]Hugo Le Baher, Vincent Lemaire, Romain Trinquart:
On the intrinsic robustness of some leading classifiers and symetric loss function - an empirical evaluation. CoRR abs/2010.13570 (2020) - [i6]Vincent Lemaire, Oumaima Alaoui Ismaili, Antoine Cornuéjols, Dominique Gay:
Predictive K-means with local models. CoRR abs/2012.09630 (2020) - [i5]Louis Desreumaux, Vincent Lemaire:
Learning active learning at the crossroads? evaluation and discussion. CoRR abs/2012.09631 (2020) - [i4]Pierre Nodet, Vincent Lemaire, Alexis Bondu, Antoine Cornuéjols, Adam Ouorou:
From Weakly Supervised Learning to Biquality Learning, a brief introduction. CoRR abs/2012.09632 (2020)
2010 – 2019
- 2019
- [c56]Alexis Bondu, Dominique Gay, Vincent Lemaire, Marc Boullé, Eole Cervenka:
FEARS: a Feature and Representation Selection approach for Time Series Classification. ACML 2019: 379-394 - [c55]Sébastien Godard, Nicolas Voisine, Tanguy Urvoy, Vincent Lemaire:
Apprentissage fédératif pour la prédiction du churn : une évaluation. EGC 2019: 141-152 - [c54]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: 328-340 - [c53]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: 26-42 - [c52]Jean Léon Bouraoui, Sonia Le Meitour, Romain Carbou, Lina Maria Rojas-Barahona, Vincent Lemaire:
Graph2Bots, Unsupervised Assistance for Designing Chatbots. SIGdial 2019: 114-117 - [i3]Dominique Gay, Vincent Lemaire:
Should we Reload Time Series Classification Performance Evaluation ? (a position paper). CoRR abs/1903.03300 (2019) - 2018
- [c51]Fabien Boitier, Jelena Pesic, Vincent Lemaire, Eric Dutisseuil, José Manuel Estarán Tolosa, Philippe Jennevé, Nicolas Le Moing, Haïk Mardoyan, Patricia Layec:
Seamless Optical Path Restoration with Just-in-Time Resource Allocation Leveraging Machine Learning. ECOC 2018: 1-3 - [c50]Vincent Lemaire, Oumaima Alaoui Ismaili:
Apport des modèles locaux pour les K-moyennes prédictives. EGC 2018: 191-202 - [c49]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: 455-458 - [e6]Georg Krempl, Vincent Lemaire, Daniel Kottke, Adrian Calma, Andreas Holzinger, Robi Polikar, Bernhard Sick:
Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning (ECML 2018) and Principles and Practice of Knowledge Discovery in Databases (PKDD 2018), Dublin, Ireland, September 10th, 2018. CEUR Workshop Proceedings 2192, CEUR-WS.org 2018 [contents] - [i2]Colin Leverger, Vincent Lemaire, Simon Malinowski, Thomas Guyet, Laurence Rozé:
Day-ahead time series forecasting: application to capacity planning. CoRR abs/1811.02215 (2018) - 2017
- [c48]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: 1-3 - [c47]Oumaima Alaoui Ismaili, Vincent Lemaire, Antoine Cornuéjols:
Un critère d'évaluation pour les K-moyennes prédictives. EGC 2017: 297-302 - [e5]Georg Krempl, Vincent Lemaire, Robi Polikar, Bernhard Sick, Daniel Kottke, Adrian Calma:
Proceedings of the Workshop and Tutorial on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2017), Skopje, Macedonia, September 18, 2017. CEUR Workshop Proceedings 1924, CEUR-WS.org 2017 [contents] - 2016
- [c46]Oumaima Alaoui Ismaili, Vincent Lemaire, Antoine Cornuéjols:
Une méthode supervisée pour initialiser les centres des K-moyennes. EGC 2016: 147-152 - [c45]Bruno Guerraz, Marc Boullé, Dominique Gay, Vincent Lemaire, Fabrice Clérot:
Analyse exploratoire par k-Coclustering avec Khiops CoViz. EGC 2016: 493-498 - [c44]Pierre-Xavier Loeffel, Vincent Lemaire, Christophe Marsala, Marcin Detyniecki:
Improving the Prediction Cost of Drift Handling Algorithms by Abstaining. ICDM Workshops 2016: 1213-1222 - [e4]Georg Krempl, Vincent Lemaire, Edwin Lughofer, Daniel Kottke:
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. CEUR Workshop Proceedings 1707, CEUR-WS.org 2016 [contents] - 2015
- [j7]Georg Krempl, Daniel Kottke, Vincent Lemaire:
Optimised probabilistic active learning (OPAL) - For fast, non-myopic, cost-sensitive active classification. Mach. Learn. 100(2-3): 449-476 (2015) - [c43]Carine Hue, Marc Boullé, Vincent Lemaire:
Online Learning of a Weighted Selective Naive Bayes Classifier with Non-convex Optimization. EGC (best of volume) 2015: 3-17 - [c42]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: 413-424 - [c41]Vincent Lemaire, Oumaima Alaoui Ismaili, Antoine Cornuéjols:
An initialization scheme for supervized K-means. IJCNN 2015: 1-8 - [c40]Christophe Salperwyck, Marc Boullé, Vincent Lemaire:
Concept drift detection using supervised bivariate grids. IJCNN 2015: 1-9 - [c39]Christian Beyer, Georg Krempl, Vincent Lemaire:
How to select information that matters: a comparative study on active learning strategies for classification. I-KNOW 2015: 2:1-2:8 - [i1]Patrick Luciano, Ismail Rebai, Vincent Lemaire:
Increasing loyalty using predictive modeling in Business-to-Business Telecommunication. CoRR abs/1506.03214 (2015) - 2014
- [j6]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): 1-10 (2014) - [c38]Vincent Lemaire, Christophe Salperwyck, Alexis Bondu:
A Survey on Supervised Classification on Data Streams. eBISS 2014: 88-125 - [c37]Oumaima Alaoui Ismaili, Vincent Lemaire, Antoine Cornuéjols:
Supervised Pre-processings Are Useful for Supervised Clustering. ECDA 2014: 147-157 - [c36]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: 1-22 - [c35]Christophe Salperwyck, Vincent Lemaire, Carine Hue:
Classifieur naïf de Bayes pondéré pour flux de données. EGC 2014: 275-286 - [c34]Carine Hue, Marc Boullé, Vincent Lemaire:
Apprentissage incrémental anytime d'un classifieur Bayésien naïf pondéré. EGC 2014: 287-298 - [c33]Oumaima Alaoui Ismaili, Vincent Lemaire, Antoine Cornuéjols:
A Supervised Methodology to Measure the Variables Contribution to a Clustering. ICONIP (1) 2014: 159-166 - [c32]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: 2600-2607 - 2013
- [c31]Christophe Salperwyck, Vincent Lemaire, Carine Hue:
Incremental Weighted Naive Bays Classifiers for Data Stream. ECDA 2013: 179-190 - [c30]Christophe Salperwyck, Marc Boullé, Vincent Lemaire:
Grille bivariée pour la détection de changement dans un flux étiqueté. EGC 2013: 389-400 - [c29]Laurent Candillier, Vincent Lemaire:
Active learning in the real-world design and analysis of the Nomao challenge. IJCNN 2013: 1-8 - [c28]Christophe Salperwyck, Vincent Lemaire:
Incremental decision tree based on order statistics. IJCNN 2013: 1-8 - [p3]Christophe Salperwyck, Vincent Lemaire:
A Two Layers Incremental Discretization Based on Order Statistics. Statistical Models for Data Analysis 2013: 315-323 - 2012
- [j5]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: 174-178 (2012) - [c27]Vincent Lemaire, Nicolas Creff, Fabrice Clérot:
K-moyennes contraintes par un classifieur. Application à la personnalisation de scores de campagnes. EGC 2012: 155-166 - [c26]Daniel L. Silver, Isabelle Guyon, Graham W. Taylor, Gideon Dror, Vincent Lemaire:
ICML2011 Unsupervised and Transfer Learning Workshop. ICML Unsupervised and Transfer Learning 2012: 1-16 - [e3]Isabelle Guyon, Gideon Dror, Vincent Lemaire, Graham W. Taylor, Daniel L. Silver:
Unsupervised and Transfer Learning - Workshop held at ICML 2011, Bellevue, Washington, USA, July 2, 2011. JMLR Proceedings 27, JMLR.org 2012 [contents] - [d1]Laurent Candillier, Vincent Lemaire:
Nomao. UCI Machine Learning Repository, 2012
- 2011
- [c25]Isabelle Guyon, Gideon Dror, Vincent Lemaire, Graham W. Taylor, David W. Aha:
Unsupervised and transfer learning challenge. IJCNN 2011: 793-800 - [c24]Christophe Salperwyck, Vincent Lemaire:
Learning with few examples: An empirical study on leading classifiers. IJCNN 2011: 1010-1019 - [c23]Isabelle Guyon, Gavin C. Cawley, Gideon Dror, Vincent Lemaire:
Results of the Active Learning Challenge. Active Learning and Experimental Design @ AISTATS 2011: 19-45 - [e2]Isabelle Guyon, Gavin C. Cawley, Gideon Dror, Vincent Lemaire, Alexander R. Statnikov:
Active Learning and Experimental Design workshop, In conjunction with AISTATS 2010, Sardinia, Italy, May 16, 2010. JMLR Proceedings 16, JMLR.org 2011 [contents] - 2010
- [j4]Alexis Bondu, Marc Boullé, Vincent Lemaire:
A non-parametric semi-supervised discretization method. Knowl. Inf. Syst. 24(1): 35-57 (2010) - [c22]Christophe Salperwyck, Vincent Lemaire:
Classification incrémentale supervisée : un panel introductif. AAFD 2010: 121-148 - [c21]Alexis Bondu, Vincent Lemaire, Marc Boullé:
Une nouvelle stratégie d'apprentissage Bayésienne. EGC 2010: 707-708 - [c20]Alexis Bondu, Vincent Lemaire, Marc Boullé:
Exploration vs. exploitation in active learning : A Bayesian approach. IJCNN 2010: 1-7 - [c19]Isabelle Guyon, Gavin C. Cawley, Gideon Dror, Vincent Lemaire:
Design and analysis of the WCCI 2010 active learning challenge. IJCNN 2010: 1-8 - [c18]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: 1-8 - [c17]Raphaël Féraud, Marc Boullé, Fabrice Clérot, Françoise Fessant, Vincent Lemaire:
The Orange Customer Analysis Platform. ICDM 2010: 584-594
2000 – 2009
- 2009
- [j3]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): 68-76 (2009) - [c16]Vincent Lemaire, Carine Hue:
Exploration des corrélations dans un classifieur - Application au placement d'offres commerciales. EGC 2009: 61-66 - [c15]Isabelle Guyon, Vincent Lemaire, Marc Boullé, Gideon Dror, David Vogel:
Analysis of the KDD Cup 2009: Fast Scoring on a Large Orange Customer Database. KDD Cup 2009: 1-22 - [e1]Gideon Dror, Marc Boullé, Isabelle Guyon, Vincent Lemaire, David Vogel:
Proceedings of KDD-Cup 2009 competition, Paris, France, June 28, 2009. JMLR Proceedings 7, JMLR.org 2009 [contents] - 2008
- [c14]Alexis Bondu, Marc Boullé, Vincent Lemaire, Stéphane Loiseau, Béatrice Duval:
A Non-parametric Semi-supervised Discretization Method. ICDM 2008: 53-62 - [c13]