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Marc Boullé
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2020 – today
- 2024
- [j19]Marc Boullé:
Floating-point histograms for exploratory analysis of large scale real-world data sets. Intell. Data Anal. 28(5): 1347-1394 (2024) - [i17]Carine Hue, Marc Boullé:
Fractional Naive Bayes (FNB): non-convex optimization for a parsimonious weighted selective naive Bayes classifier. CoRR abs/2409.11100 (2024) - 2023
- [j18]Valentina Zelaya Mendizábal, Marc Boullé, Fabrice Rossi:
Fast and fully-automated histograms for large-scale data sets. Comput. Stat. Data Anal. 180: 107668 (2023) - [c89]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 - [c88]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 - [i16]Marc Boullé:
Two-level histograms for dealing with outliers and heavy tail distributions. CoRR abs/2306.05786 (2023) - [i15]Vincent Lemaire, Fabrice Clérot, Marc Boullé:
An Efficient Shapley Value Computation for the Naive Bayes Classifier. CoRR abs/2307.16718 (2023) - 2022
- [c87]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 - [i14]Aichetou Bouchareb, Marc Boullé, Fabrice Clérot, Fabrice Rossi:
Model Based Co-clustering of Mixed Numerical and Binary Data. CoRR abs/2212.11725 (2022) - [i13]Aichetou Bouchareb, Marc Boullé, Fabrice Clérot, Fabrice Rossi:
Co-clustering based exploratory analysis of mixed-type data tables. CoRR abs/2212.11728 (2022) - [i12]Valentina Zelaya Mendizábal, Marc Boullé, Fabrice Rossi:
Fast and fully-automated histograms for large-scale data sets. CoRR abs/2212.13524 (2022) - 2021
- [c86]Dominique Gay, Alexis Bondu, Vincent Lemaire, Marc Boullé:
Interpretable Feature Construction for Time Series Extrinsic Regression. PAKDD (1) 2021: 804-816 - [i11]Dominique Gay, Alexis Bondu, Vincent Lemaire, Marc Boullé:
Interpretable Feature Construction for Time Series Extrinsic Regression. CoRR abs/2103.10247 (2021) - 2020
- [c85]Dominique Gay, Alexis Bondu, Vincent Lemaire, Marc Boullé, Fabrice Clérot:
Multivariate Time Series Classification: A Relational Way. DaWaK 2020: 316-330 - [c84]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
2010 – 2019
- 2019
- [j17]Marc Boullé, Clément Charnay, Nicolas Lachiche
:
A scalable robust and automatic propositionalization approach for Bayesian classification of large mixed numerical and categorical data. Mach. Learn. 108(2): 229-266 (2019) - [c83]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 - [p3]Isabelle Guyon, Lisheng Sun-Hosoya, Marc Boullé, Hugo Jair Escalante, Sergio Escalera
Analysis of the AutoML Challenge Series 2015-2018. Automated Machine Learning 2019: 177-219 - [i10]Aichetou Bouchareb, Marc Boullé, Fabrice Rossi, Fabrice Clérot:
Un modèle Bayésien de co-clustering de données mixtes. CoRR abs/1902.02056 (2019) - 2018
- [j16]Romain Guigourès, Marc Boullé, Fabrice Rossi
Discovering patterns in time-varying graphs: a triclustering approach. Adv. Data Anal. Classif. 12(3): 509-536 (2018) - [j15]Marc Boullé:
Hierarchical two-part MDL code for multinomial distributions. Int. J. Approx. Reason. 103: 71-93 (2018) - [c82]Aichetou Bouchareb, Marc Boullé, Fabrice Clérot, Fabrice Rossi:
Model Based Co-clustering of Mixed Numerical and Binary Data. EGC (best of volume) 2018: 3-22 - [c81]Aichetou Bouchareb, Marc Boullé, Fabrice Clérot, Fabrice Rossi:
Co-clustering Based Exploratory Analysis of Mixed-Type Data Tables. EGC (best of volume) 2018: 23-41 - [c80]Marius Barctus, Marc Boullé, Fabrice Clérot:
A two level co-clustering algorithm for very large data sets. EGC 2018: 95-106 - [c79]Aichetou Bouchareb, Marc Boullé, Fabrice Rossi, Fabrice Clérot:
Un modèle Bayésien de co-clustering de données mixtes. EGC 2018: 275-280 - 2017
- [j14]Elias Egho
A user parameter-free approach for mining robust sequential classification rules. Knowl. Inf. Syst. 52(1): 53-81 (2017) - [c78]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 - [c77]Aichetou Bouchareb, Marc Boullé, Fabrice Rossi:
Co-clustering de données mixtes à base des modèles de mélange. EGC 2017: 141-152 - [c76]Aichetou Bouchareb, Marc Boullé, Fabrice Clérot, Fabrice Rossi:
Application du coclustering à l'analyse exploratoire d'une table de données. EGC 2017: 177-188 - [c75]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 - 2016
- [c74]Bruno Guerraz, Marc Boullé, Dominique Gay, Vincent Lemaire, Fabrice Clérot:
Analyse exploratoire par k-Coclustering avec Khiops CoViz. EGC 2016: 493-498 - [c73]Marc Boullé:
Khiops: outil d'apprentissage supervisé automatique pour la fouille de grandes bases de données multi-tables. EGC 2016: 505-510 - [c72]Marc Boullé:
Predicting Dangerous Seismic Events in Coal Mines under Distribution Drift. FedCSIS 2016: 221-224 - [i9]Marc Boullé, Fabrice Clérot, Carine Hue:
Revisiting enumerative two-part crude MDL for Bernoulli and multinomial distributions (Extended version). CoRR abs/1608.05522 (2016) - [i8]Romain Guigourès, Marc Boullé, Fabrice Rossi:
Discovering Patterns in Time-Varying Graphs: A Triclustering Approach. CoRR abs/1608.07929 (2016) - 2015
- [c71]Dominique Gay, Romain Guigourès, Marc Boullé, Fabrice Clérot:
TESS: Temporal event sequence summarization. DSAA 2015: 1-10 - [c70]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 - [c69]Marc Boullé:
Tagging fireworkers activities from body sensors under distribution drift. FedCSIS 2015: 389-396 - [c68]Elias Egho, Dominique Gay
A Parameter-Free Approach for Mining Robust Sequential Classification Rules. ICDM 2015: 745-750 - [c67]Christophe Salperwyck, Marc Boullé, Vincent Lemaire:
Concept drift detection using supervised bivariate grids. IJCNN 2015: 1-9 - [c66]Alexis Bondu, Marc Boullé, Antoine Cornuéjols:
Symbolic Representation of Time Series: A Hierarchical Coclustering Formalization. AALTD@PKDD/ECML 2015 - [c65]Alexis Bondu, Marc Boullé, Antoine Cornuéjols:
Symbolic Representation of Time Series: A Hierarchical Coclustering Formalization. AALTD@PKDD/ECML (Revised Selected Papers) 2015: 3-16 - [c64]Romain Guigourès, Dominique Gay
Country-Scale Exploratory Analysis of Call Detail Records Through the Lens of Data Grid Models. ECML/PKDD (3) 2015: 37-52 - [c63]Marc Boullé:
Prediction of Methane Outbreak in Coal Mines from Historical Sensor Data under Distribution Drift. RSFDGrC 2015: 439-451 - [i7]Romain Guigourès, Dominique Gay, Marc Boullé, Fabrice Clérot, Fabrice Rossi:
Country-scale Exploratory Analysis of Call Detail Records through the Lens of Data Grid Models. CoRR abs/1503.06060 (2015) - [i6]Dominique Gay, Romain Guigourès, Marc Boullé, Fabrice Clérot:
Cats & Co: Categorical Time Series Coclustering. CoRR abs/1505.01300 (2015) - [i5]Marc Boullé:
Universal Approximation of Edge Density in Large Graphs. CoRR abs/1508.01340 (2015) - [i4]Romain Guigourès, Marc Boullé, Fabrice Rossi:
A Study of the Spatio-Temporal Correlations in Mobile Calls Networks. CoRR abs/1510.09005 (2015) - [i3]Mohamed Khalil El Mahrsi, Romain Guigourès, Fabrice Rossi, Marc Boullé:
Co-Clustering Network-Constrained Trajectory Data. CoRR abs/1511.01281 (2015) - 2014
- [c62]Romain Guigourès, Dominique Gay, Marc Boullé, Fabrice Clérot:
Clustering de séquences d'évènements temporels. EGC 2014: 191-202 - [c61]Carine Hue, Marc Boullé, Vincent Lemaire:
Apprentissage incrémental anytime d'un classifieur Bayésien naïf pondéré. EGC 2014: 287-298 - [c60]Marc Boullé:
Parsimonious Naive Bayes. FedCSIS 2014: 355-359 - [c59]Marc Boullé:
Towards Automatic Feature Construction for Supervised Classification. ECML/PKDD (1) 2014: 181-196 - [c58]Bruno Guerraz, Marc Boullé, Dominique Gay, Fabrice Clérot:
Khiops CoViz: A Tool for Visual Exploratory Analysis of k-Coclustering Results. ECML/PKDD (3) 2014: 444-447 - [i2]Marc Boullé, Romain Guigourès, Fabrice Rossi:
Nonparametric Hierarchical Clustering of Functional Data. CoRR abs/1407.0612 (2014) - 2013
- [c57]Romain Guigourès, Marc Boullé, Fabrice Rossi
A Study of the Spatio-Temporal Correlations in Mobile Calls Networks. EGC (best of volume) 2013: 3-17 - [c56]Mohamed Khalil El Mahrsi, Romain Guigourès, Fabrice Rossi
Co-Clustering Network-Constrained Trajectory Data. EGC (best of volume) 2013: 19-32 - [c55]Marc Boullé, Dhafer Lahbib:
Vers une Automatisation de la Construction de Variables pour la Classification Supervisée. EGC 2013: 25-36 - [c54]Dhafer Lahbib, Marc Boullé, Dominique Laurent:
Un Critère d'Évaluation pour la Construction de Variables à base d'Itemsets pour l'Apprentissage Supervisé Multi-Tables. EGC 2013: 85-90 - [c53]Mohamed Khalil El Mahrsi, Romain Guigourès, Fabrice Rossi, Marc Boullé:
Classifications croisées de données de trajectoires contraintes par un réseau routier. EGC 2013: 341-352 - [c52]Dominique Gay, Marc Boullé:
Construction de descripteurs à partir du coclustering pour la classification supervisée de séries temporelles. EGC 2013: 353-364 - [c51]Christophe Salperwyck, Marc Boullé, Vincent Lemaire:
Grille bivariée pour la détection de changement dans un flux étiqueté. EGC 2013: 389-400 - [c50]Romain Guigourès, Marc Boullé, Fabrice Rossi:
Étude des corrélations spatio-temporelles des appels mobiles en France. EGC 2013: 437-448 - [c49]Alexis Bondu, Marc Boullé, Benoît Grossin:
SAXO: An optimized data-driven symbolic representation of time series. IJCNN 2013: 1-9 - [c48]Dominique Gay, Romain Guigourès, Marc Boullé, Fabrice Clérot:
Feature Extraction over Multiple Representations for Time Series Classification. NFMCP 2013: 18-34 - [i1]Romain Guigourès, Marc Boullé, Fabrice Rossi:
A Triclustering Approach for Time Evolving Graphs. CoRR abs/1301.2659 (2013) - 2012
- [j13]Marc Boullé:
Functional data clustering via piecewise constant nonparametric density estimation. Pattern Recognit. 45(12): 4389-4401 (2012) - [c47]Marc Boullé, Romain Guigourès, Fabrice Rossi
Nonparametric Hierarchical Clustering of Functional Data. EGC (best of volume) 2012: 15-35 - [c46]Marc Boullé:
Sélection Bayésienne de Modèles avec Prior Dépendant des Données. EGC 2012: 29-34 - [c45]Dhafer Lahbib, Marc Boullé, Dominique Laurent:
Supervised Pre-processing of Numerical Variables for Multi-Relational Data Mining. EGC (best of volume) 2012: 95-109 - [c44]Marc Boullé, Romain Guigourès, Fabrice Rossi:
Clustering hiérarchique non paramétrique de données fonctionnelles. EGC 2012: 101-112 - [c43]Dhafer Lahbib, Marc Boullé, Dominique Laurent:
Prétraitement Supervisé des Variables Numériques pour la Fouille de Données Multi-Tables. EGC 2012: 501-512 - [c42]Romain Guigourès, Marc Boullé, Fabrice Rossi
A Triclustering Approach for Time Evolving Graphs. ICDM Workshops 2012: 115-122 - [c41]Dhafer Lahbib, Marc Boullé, Dominique Laurent:
Itemset-Based Variable Construction in Multi-relational Supervised Learning. ILP 2012: 130-150 - [c40]Dominique Gay, Marc Boullé:
A Bayesian Approach for Classification Rule Mining in Quantitative Databases. ECML/PKDD (2) 2012: 243-259 - 2011
- [c39]Romain Guigourès, Marc Boullé:
Optimisation directe des poids de modèles dans un prédicteur Bayésien naïf moyenné. EGC 2011: 77-82 - [c38]Alexis Bondu, Marc Boullé:
Détection de changements de distribution dans un flux de données : une approche supervisée. EGC 2011: 191-196 - [c37]Marc Boullé:
Estimation de la densité d'arcs dans les graphes de grande taille : une alternative à la détection de clusters. EGC 2011: 353-364 - [c36]Dhafer Lahbib, Marc Boullé, Dominique Laurent:
Sélection des variables informatives pour l'apprentissage supervisé multi-tables. EGC 2011: 425-430 - [c35]Dominique Gay, Marc Boullé:
Un critère Bayésien pour évaluer la robustesse des règles de classification. EGC 2011: 539-550 - [c34]Alexis Bondu, Marc Boullé:
A supervised approach for change detection in data streams. IJCNN 2011: 519-526 - [c33]Dhafer Lahbib, Marc Boullé, Dominique Laurent:
Informative Variables Selection for Multi-relational Supervised Learning. MLDM 2011: 75-87 - [c32]Dominique Gay, Marc Boullé:
A Bayesian Criterion for Evaluating the Robustness of Classification Rules in Binary Data Sets. EGC (best of volume) 2011: 3-21 - 2010
- [j12]Alexis Bondu, Marc Boullé, Vincent Lemaire:
A non-parametric semi-supervised discretization method. Knowl. Inf. Syst. 24(1): 35-57 (2010) - [j11]Sylvain Ferrandiz, Marc Boullé:
Bayesian instance selection for the nearest neighbor rule. Mach. Learn. 81(3): 229-256 (2010) - [c31]Françoise Fessant, Aurélie Le Cam, Marc Boullé, Raphaël Féraud:
Modelling Complex Data by Learning Which Variable to Construct. DaWak 2010: 324-335 - [c30]Marc Boullé:
Simultaneous Partitioning of Input and Class Variables for Supervised Classification Problems with Many Classes. EGC (best of volume) 2010: 105-119 - [c29]Marc Boullé:
Classification supervisée pour de grands nombres de valeurs à prédire. EGC 2010: 537-548 - [c28]Alexis Bondu, Vincent Lemaire, Marc Boullé:
Une nouvelle stratégie d'apprentissage Bayésienne. EGC 2010: 707-708 - [c27]Alexis Bondu, Vincent Lemaire, Marc Boullé:
Exploration vs. exploitation in active learning : A Bayesian approach. IJCNN 2010: 1-7 - [c26]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 - [c25]Raphaël Féraud, Marc Boullé, Fabrice Clérot, Françoise Fessant, Vincent Lemaire:
The Orange Customer Analysis Platform. ICDM 2010: 584-594
2000 – 2009
- 2009
- [j10]Marc Boullé:
Optimum simultaneous discretization with data grid models in supervised classification: a Bayesian model selection approach. Adv. Data Anal. Classif. 3(1): 39-61 (2009) - [j9]Marc Boullé:
A Parameter-Free Classification Method for Large Scale Learning. J. Mach. Learn. Res. 10: 1367-1385 (2009) - [j8]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) - [c24]Nicolas Voisine, Marc Boullé, Carine Hue:
A Bayes Evaluation Criterion for Decision Trees. EGC (best of volume) 2009: 21-38 - [c23]Nicolas Voisine, Marc Boullé, Carine Hue:
Un critère d'évaluation Bayésienne pour la construction d'arbre de décision. EGC 2009: 67-78 - [c22]Marc Boullé:
Une méthode de classification supervisée sans paramètre pour l'apprentissage sur les grandes bases de données. EGC 2009: 259-264 - [c21]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 - [p2]Damien Poirier, Françoise Fessant, Cécile Bothorel, Emilie Guimier De Neef, Marc Boullé:
Approches Statistique et Linguistique Pour la Classification de Textes d'Opinion Portant sur les Films. Fouille de Données d'Opinions 2009: 144-167 - [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
- [c20]Marc Boullé:
Khiops : outil de préparation et modélisation des données pour la fouille des grandes bases de données. EGC 2008: 229-230 - [c19]Raphaël Féraud, Marc Boullé, Fabrice Clérot, Françoise Fessant:
Vers l'exploitation de grandes masses de données. EGC 2008: 241-252 - [c18]Damien Poirier, Cécile Bothorel, Marc Boullé:
Analyse exploratoire d'opinions cinématographiques : co-clustering de corpus textuels communautaires. EGC 2008: 565-576 - [c17]Alexis Bondu, Marc Boullé, Vincent Lemaire, Stéphane Loiseau, Béatrice Duval:
A Non-parametric Semi-supervised Discretization Method. ICDM 2008: 53-62 - 2007
- [j7]Marc Boullé:
Compression-Based Averaging of Selective Naive Bayes Classifiers. J. Mach. Learn. Res. 8: 1659-1685 (2007) - [j6]Carine Hue, Marc Boullé:
A New Probabilistic Approach in Rank Regression with Optimal Bayesian Partitioning. J. Mach. Learn. Res. 8: 2727-2754 (2007) - [c16]Carine Hue, Marc Boullé:
Une approche non paramétrique Bayesienne pour l'estimation de densité conditionnelle sur les rangs. EGC 2007: 111-122 - [c15]Sylvain Ferrandiz, Marc Boullé:
Evaluation supervisée de métrique : application à la préparation de données séquentielles. EGC 2007: 319-330 - [c14]Marc Boullé:
Une méthode optimale d'évaluation bivariée pour la classification supervisée. EGC 2007: 461-472 - [c13]Marc Boullé:
Report on Preliminary Experiments with Data Grid Models in the Agnostic Learning vs. Prior Knowledge Challenge. IJCNN 2007: 3092-3097 - [c12]Laurent Candillier, Frank Meyer, Marc Boullé:
Comparing State-of-the-Art Collaborative Filtering Systems. MLDM 2007: 548-562 - 2006
- [j5]Sylvain Ferrandiz, Marc Boullé:
Supervised evaluation of Voronoi partitions. Intell. Data Anal. 10(3): 269-283 (2006) - [j4]Marc Boullé:
MODL: A Bayes optimal discretization method for continuous attributes. Mach. Learn. 65(1): 131-165 (2006) - [c11]Marc Boullé, Carine Hue:
Optimal Bayesian 2D-Discretization for Variable Ranking in Regression. Discovery Science 2006: 53-64 - [c10]Sylvain Ferrandiz, Marc Boullé:
Sélection supervisée d'instances : une approche descriptive. EGC 2006: 421-432 - [c9]Marc Boullé:
Regularization and Averaging of the Selective Naive Bayes classifier. IJCNN 2006: 1680-1688 - [c8]Sylvain Ferrandiz, Marc Boullé:
Supervised Selection of Dynamic Features, with an Application to Telecommunication Data Preparation. ICDM 2006: 239-249 - [p1]Marc Boullé:
An Enhanced Selective Naïve Bayes Method with Optimal Discretization. Feature Extraction 2006: 499-507 - 2005
- [j3]Marc Boullé:
Optimal bin number for equal frequency discretizations in supervized learning. Intell. Data Anal. 9(2): 175-188 (2005) - [j2]Marc Boullé:
A Bayes Optimal Approach for Partitioning the Values of Categorical Attributes. J. Mach. Learn. Res. 6: 1431-1452 (2005) - [c7]Marc Boullé:
A Grouping Method for Categorical Attributes Having Very Large Number of Values. MLDM 2005: 228-242 - [c6]Sylvain Ferrandiz, Marc Boullé:
Multivariate Discretization by Recursive Supervised Bipartition of Graph. MLDM 2005: 253-264 - [c5]Sylvain Ferrandiz, Marc Boullé:
Supervised Evaluation of Dataset Partitions: Advantages and Practice. MLDM 2005: 600-609 - 2004
- [j1]Marc Boullé:
Khiops: A Statistical Discretization Method of Continuous Attributes. Mach. Learn. 55(1): 53-69 (2004) - [c4]Marc Boullé:
A robust method for partitioning the values of categorical attributes. EGC 2004: 173-184 - [c3]Sylvain Ferrandiz, Marc Boullé:
Utilisation des graphes de proximité dans le cadre de l'apprentissage basé sur les voisins. EGC 2004: 355-366 - 2003
- [c2]Marc Boullé:
Khiops: A Discretization Method of Continuous Attributes with Guaranteed Resistance to Noise. MLDM 2003: 50-64 - 2002
- [c1]Marc Boullé:
Khiops: une méthode statistique de discrétisation. EGC 2002: 107-118
Coauthor Index
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