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ORCIDNicolas Voisine
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2020 – today
- 2025
[c17]Nathan Le Boudec, Nicolas Voisine, Bruno Crémilleux:
Évaluation de l'uplift multi-traitement sur des données biaisées dans le cas du non-random assignment. EGC 2025: 27-38- [c16]Nicolas Voisine, Lou-Anne Quellet, Marc Boullé, Fabrice Clérot, Anais Collin:
Sélection de variables secondaires de données multi-tables pour la classification. EGC 2025: 195-206 - [c15]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, Vincent Lemaire:
Khiops: apprentissage automatique sans hyperparamètre. EGC 2025: 575-582 - [i1]Marc Boullé, Nicolas Voisine, Bruno Guerraz, Carine Hue, Felipe Olmos, Vladimir Popescu, Stéphane Gouache, Stéphane Bouget, Alexis Bondu, Luc-Aurélien Gauthier, Noureddine Yacine Nair Benrekia, Fabrice Clérot, Vincent Lemaire:
Khiops: An End-to-End, Frugal AutoML and XAI Machine Learning Solution for Large, Multi-Table Databases. CoRR abs/2508.20519 (2025) - 2023
- [c14]Mina Rafla, Nicolas Voisine, Bruno Crémilleux, Marc Boullé:
Une approche bayésienne non paramétrique de sélection de variables pour la modélisation de l'uplift. EGC 2023: 523-530 - [c13]Mina Rafla, Nicolas Voisine, Bruno Crémilleux:
Parameter-Free Bayesian Decision Trees for Uplift Modeling. PAKDD (2) 2023: 309-321 - [c12]Mina Rafla, Nicolas Voisine, Bruno Crémilleux:
A Parameter-Free Bayesian Framework for Uplift Modeling Application on Telecom Data. PKDD/ECML Workshops (4) 2023: 277-291 - 2022
- [c11]Mina Rafla, Nicolas Voisine, Bruno Crémilleux:
Evaluation de l'uplift sur des données biaisées dans le cas du Non-Random Assignment. EGC 2022: 51-62 - [c10]Mina Rafla, Nicolas Voisine, Bruno Crémilleux:
Evaluation of Uplift Models with Non-Random Assignment Bias. IDA 2022: 251-263 - [c9]Mina Rafla, Nicolas Voisine, Bruno Crémilleux, Marc Boullé:
A Non-parametric Bayesian Approach for Uplift Discretization and Feature Selection. ECML/PKDD (5) 2022: 239-254
2010 – 2019
- 2019
- [c8]Sébastien Godard, Nicolas Voisine, Tanguy Urvoy, Vincent Lemaire:
Apprentissage fédératif pour la prédiction du churn : une évaluation. EGC 2019: 141-152 - 2017
- [j1]Elias Egho
, Dominique Gay, Marc Boullé, Nicolas Voisine, Fabrice Clérot:
A user parameter-free approach for mining robust sequential classification rules. Knowl. Inf. Syst. 52(1): 53-81 (2017) - [c7]Elias Egho, Dominique Gay, Romain Trinquart, Marc Boullé, Nicolas Voisine, Fabrice Clérot:
MiSeRe-Hadoop: A Large-Scale Robust Sequential Classification Rules Mining Framework. DaWaK 2017: 105-119 - [c6]Sènami C. Fréjus Ahomagnon, Nicolas Voisine, Marc Boullé:
Sélection et transformation de variables pour la classification Multi-Label par une approche MDL. EGC 2017: 345-350 - 2015
- [c5]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 - [c4]Elias Egho, Dominique Gay, Marc Boullé, Nicolas Voisine, Fabrice Clérot:
A Parameter-Free Approach for Mining Robust Sequential Classification Rules. ICDM 2015: 745-750
2000 – 2009
- 2009
- [c3]Nicolas Voisine, Marc Boullé, Carine Hue:
A Bayes Evaluation Criterion for Decision Trees. EGC (best of volume) 2009: 21-38 - [c2]Nicolas Voisine, Marc Boullé, Carine Hue:
Un critère d'évaluation Bayésienne pour la construction d'arbre de décision. EGC 2009: 67-78 - 2008
- [c1]Vincent Lemaire, Raphaël Féraud, Nicolas Voisine:
Contact personalization using a score understanding method. IJCNN 2008: 649-654
Coauthor Index
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