Vincent Vandewalle

Matthieu Marbac, Mohammed Sedki, Christophe Biernacki, Vincent Vandewalle. Simultaneous semi-parametric estimation of clustering and regression. Journal of Computational and Graphical Statistics, Taylor & Francis, In press. ⟨hal-03090573v2⟩

Adrien Ehrhardt, Christophe Biernacki, Vincent Vandewalle, Philippe Heinrich, Sébastien Beben. Reject Inference Methods in Credit Scoring. Journal of Applied Statistics, Taylor & Francis (Routledge), 2021. ⟨hal-03087279v2⟩

Christophe Biernacki, Matthieu Marbac, Vincent Vandewalle. Gaussian Based Visualization of Gaussian and Non-Gaussian Based Clustering. Journal of Classification, Springer Verlag, 2020, ⟨10.1007/s00357-020-09369-y⟩. ⟨hal-01949155v3⟩

Vincent Vandewalle. Multi-Partitions Subspace Clustering. Mathematics , MDPI, 2020, 8 (4), pp.597. ⟨10.3390/math8040597⟩. ⟨hal-03117603⟩

Florent Dewez, Benjamin Guedj, Vincent Vandewalle. From industry-wide parameters to aircraft-centric on-flight inference: improving aeronautics performance prediction with machine learning. Data-Centric Engineering, Cambridge University Press, 2020, ⟨10.1017/dce.2020.12⟩. ⟨hal-02570875⟩

Marie Cuvelliez, Vincent Vandewalle, Maxime Brunin, Olivia Beseme, Audrey Hulot, et al.. Circulating proteomic signature of early death in heart failure patients with reduced ejection fraction. Scientific Reports, Nature Publishing Group, 2019, 9, pp.19202. ⟨10.1038/s41598-019-55727-1⟩. ⟨hal-02414293v2⟩

Matthieu Marbac, Vincent Vandewalle. A tractable Multi-Partitions Clustering. Computational Statistics and Data Analysis, Elsevier, 2018, ⟨10.1016/j.csda.2018.06.013⟩. ⟨hal-01691417⟩

Matthieu Marbac, Christophe Biernacki, Vincent Vandewalle. Model-based clustering of Gaussian copulas for mixed data. Communications in Statistics - Theory and Methods, Taylor & Francis, 2017, 46 (23), pp.11635-11656. ⟨10.1080/03610926.2016.1277753⟩. ⟨hal-00987760v4⟩

Matthieu Marbac, Christophe Biernacki, Vincent Vandewalle. Latent class model with conditional dependency per modes to cluster categorical data. Advances in Data Analysis and Classification, Springer Verlag, 2016, 10 (2), pp.183-207. ⟨10.1007/s11634-016-0250-1⟩. ⟨hal-00950112v2⟩

Matthieu Marbac, Christophe Biernacki, Vincent Vandewalle. Model-based clustering for conditionally correlated categorical data. Journal of Classification, Springer Verlag, 2015, 2 (32), pp.145-175. ⟨10.1007/s00357⟩. ⟨hal-00787757v3⟩

Emil Eirola, Amaury Lendasse, Vincent Vandewalle, Christophe Biernacki. Mixture of Gaussians for Distance Estimation with Missing Data. Neurocomputing, Elsevier, 2014, 131, pp.32-42. ⟨10.1016/j.neucom.2013.07.050⟩. ⟨hal-00921023v2⟩

Vincent Vandewalle, Christophe Biernacki, Gilles Celeux, Gérard Govaert. A predictive deviance criterion for selecting a generative model in semi-supervised classification. Computational Statistics and Data Analysis, Elsevier, 2013, 64, pp.220-236. ⟨inria-00516991⟩

Vincent Vandewalle, Christophe Biernacki, Gilles Celeux, Gérard Govaert. A predictive deviance criterion for selecting a generative model in semi-supervised classification. Computational Statistics and Data Analysis, Elsevier, 2013, 64, pp.220-236. ⟨10.1016/j.csda.2013.02.010⟩. ⟨hal-00778130⟩

Gérard Grégoire, François-Xavier Jollois, Jean-François Petiot, Abdellah Qannari, Serge Sabourin, et al.. Les logiciels et l'enseignement de la statistique dans les départements " Statistique et Informatique Décisionnelle " (STID) des IUT. Statistique et Enseignement, Société Française de Statistique, 2012, 2 (2), pp.5-24. ⟨hal-00913110⟩

Stephane Robin, Sophie Schbath, Vincent Vandewalle. Statistical tests to compare motif count exceptionalities. BMC Bioinformatics, BioMed Central, 2007, 8, pp.84. ⟨10.1186/1471-2105-8-84⟩. ⟨hal-01197501⟩

Christophe Biernacki, Matthieu Marbac Lourdelle, Vincent Vandewalle. Gaussian Based Visualization of Gaussian and Non-Gaussian Based Clustering. MIMO 2021: Workshop on Mixture Models, Apr 2021, Rouen, France. ⟨hal-03505667⟩

Wilfried Heyse, Vincent Vandewalle, Philippe Amouyel, Guillemette Marot, Christophe Bauters, et al.. Support of temporal structure in the statistical analysis of high-throughput proteomic data. Journées de Statistique 2021, Jun 2021, Nice, France. ⟨hal-03525345⟩

Christophe Biernacki, Claire Boyer, Gilles Celeux, Julie Josse, Fabien Laporte, et al.. Impact of Missing Data on Mixtures and Clustering. MHC2021 - Mixtures, Hidden Markov Models, Clustering, Jun 2021, Orsay, France. ⟨hal-03505664⟩

Vincent Vandewalle, Alexandre Caron, Benoît Dervaux. Estimation du nombre de problèmes et détermination du nombre de sujets nécessaires dans les études d’utilisabilité : une approche bayésienne. Journées Biostatistiques 2020 - GDR « Statistiques & santé », Oct 2020, Paris, France. ⟨hal-03118164⟩

Christophe Biernacki, Matthieu Marbac-Lourdelle, Vincent Vandewalle. Gaussian Based Visualization of Gaussian and Non-Gaussian Based Clustering. 3rd International Conference on Econometrics and Statistics (EcoSta 2019), Jun 2019, Taichung, Taiwan. ⟨hal-02398999⟩

Adrien Ehrhardt, Vincent Vandewalle, Christophe Biernacki, Philippe Heinrich. Supervised multivariate discretization and levels merging for logistic regression. 23rd International Conference on Computational Statistics, Aug 2018, Iasi, Romania. ⟨hal-01949128⟩

Vincent Vandewalle, Cristian Preda, Sophie Dabo. Clustering spatial functional data. ERCIM 2018, Dec 2018, Pise, Italy. ⟨hal-01956923⟩

Vincent Vandewalle, Matthieu Marbac. A tractable multi-partitions clustering. COMPSTAT 2018 - 23rd International Conference on Computational Statistics, Aug 2018, Iasi, Romania. ⟨hal-01956922⟩

Christophe Biernacki, Vincent Vandewalle, Matthieu Marbac. Gaussian-based visualization of Gaussian and non-Gaussian model-based clustering. 23rd International Conference on Computational Statistics, Aug 2018, Iasi, Romania. ⟨hal-01949127⟩

Vincent Vandewalle. Simultaneous dimension reduction and multi-objective clustering . IFCS 2017 - Conference of the International Federation of Classification Societies, Aug 2017, Tokyo, Japan. pp.1-29. ⟨hal-01662271⟩

Vincent Vandewalle, Christophe Biernacki. Survival analysis with complex covariates: a model-based clustering preprocessing step. IEEE PHM 2017, Jun 2017, Dallas, United States. ⟨hal-01667588⟩

Vincent Vandewalle, Thierry Mottet, Matthieu Marbac. Model-based variable clustering. CMStatistics/ERCIM 2017 - 10th International Conference of the ERCIM WG on Computational and Methodological Statistics, Dec 2017, London, United Kingdom. pp.1-19. ⟨hal-01691421⟩

Serge Iovleff, Mathieu Fauvel, Stéphane Girard, Cristian Preda, Vincent Vandewalle. Mixture Models with Missing data Classication of Satellite Image Time Series: QUALIMADOS: Atelier Qualité des masses de données scientiques. Journées Science des Données MaDICS 2017, Jun 2017, Marseille, France. pp.1-60. ⟨hal-01649206⟩

Vincent Vandewalle, Christophe Biernacki. Dealing with missing data through mixture models. ICB Seminars 2017 - 154th Seminar on ”Statistics and clinical practice”, May 2017, Varsovie, Poland. pp.1-3. ⟨hal-01667614⟩

Christophe Biernacki, Gwenaelle Castellan, Stephane Chretien, Benjamin Guedj, Vincent Vandewalle. Pitfalls in Mixtures from the Clustering Angle. Working Group on Model-Based Clustering Summer Session, Jul 2016, Paris, France. ⟨hal-01419755⟩

Vincent Vandewalle, Cristina Cozma, Cristian Preda. Clustering categorical functional data Application to medical discharge letters. 8th International Conference of the ERCIM WG on Computational and Methodological Statistics, Dec 2015, Londres, France. ⟨hal-01251284⟩

Vincent Vandewalle, C Biernacki. An efficient SEM algorithm for Gaussian Mixtures with missing data. 8th International Conference of the ERCIM WG on Computational and Methodological Statistics, Dec 2015, Londres, United Kingdom. ⟨hal-01242588⟩

Matthieu Marbac, Christophe Biernacki, Vincent Vandewalle. Model-based clustering of categorical data by relaxing conditional independence. Classification Society Meeting, Mc Master University, Jun 2015, Hamilton, Ontario, Canada. ⟨hal-01238334⟩

Vincent Vandewalle. Sélection prédictive d'un modèle génératif par le critère AICp. 41èmes Journées de Statistique, SFdS, Bordeaux, 2009, Bordeaux, France, France. ⟨inria-00386678⟩

Vincent Vandewalle. Simultaneous dimension reduction and multi-objective clustering. Statlearn’17, Lyon: 4-7 april 2017, Apr 2017, Lyon, France. ⟨hal-03183333⟩

Adrien Ehrhardt, Christophe Biernacki, Vincent Vandewalle, Philippe Heinrich. Model-based multivariate discretization for logistic regression. Data Science Summer School, Aug 2017, Paris, France. 2017. ⟨hal-02075126⟩

Vincent Vandewalle, Cristian Preda. Clustering categorical functional data Application to medical discharge letters Medical discharge letters. Working Group on Model-Based Clustering Summer Session: Paris, July 17-23, 2016, Jul 2016, Paris, France. 0010. ⟨hal-01424950⟩

Christophe Biernacki, Vincent Vandewalle. Label switching in mixtures. Working Group on Model-Based Clustering Summer Session: Glasgow, July 17-23, 2011, Jul 2011, Glasgow, United Kingdom, France. ⟨hal-03183299⟩

Vincent Vandewalle. Simultaneous dimension reduction and multi-objective clustering using probabilistic factorial discriminant analysis. CMStatistics 2016, Dec 2016, Sevilla, Spain. ⟨hal-01424965⟩

Chloé Friguet, Frédérique Letué, Vincent Vandewalle. Table ronde : “pourquoi et comment enseigner l’analyse de données massives (big data)”. 47èmes Journées de Statistique de la SFdS, Jun 2015, Lille, France. ⟨hal-01250812⟩

Vincent Vandewalle, Cristian Preda, Sophie Dabo-Niang. Clustering spatial functional data. J. Mateu and R. Giraldo. Geostatistical Functional Data Analysis : Theory and Methods. Editors: Jorge Mateu, Ramon Giraldo, John Wiley and Sons, Chichester. ISBN : 978-1-119-38784-8, 2021, Geostatistical Functional Data Analysis : Theory and Methods. ⟨hal-01948934⟩

Cristian Preda, Quentin Grimonprez, Vincent Vandewalle. cfda: an R Package for Categorical Functional Data Analysis. 2020. ⟨hal-02973094⟩

Florent Dewez, Benjamin Guedj, Arthur Talpaert, Vincent Vandewalle. An end-to-end data-driven optimisation framework for constrained trajectories. 2020. ⟨hal-03024720⟩

Adrien Ehrhardt, Christophe Biernacki, Vincent Vandewalle, Philippe Heinrich. Feature quantization for parsimonious and interpretable predictive models. 2019. ⟨hal-01949135v2⟩

Vincent Vandewalle. Estimation et sélection en classification semi-supervisée. Mathématiques [math]. Université des Sciences et Technologie de Lille - Lille I, 2009. Français. ⟨tel-00447141⟩

Vincent Vandewalle. Contribution to model-based clustering of heterogeneous data. Statistics [math.ST]. Université de Lille, 2021. ⟨tel-03118189⟩