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Publications Charles Bouveyron > Publications

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Preprints (5)

- C. Bouveyron, J. Delon and A. Houdard, High-Dimensional Mixture Models for Unsupervised Image Denoising (HDMI), Preprint HAL n°01544249, Université Paris Descartes, 2017: [pdf].
- C. Bouveyron, L. Bozzi, J. Jacques and F.-X. Jollois, The Functional Latent Block Model for the Co-Clustering of Electricity Consumption Curves, Preprint HAL n°01533438, Université Paris Descartes, 2017: [pdf].
- C. Bouveyron, P. Latouche and P.-A. Mattei, Exact Dimensionality Selection fo Bayesian PCA, Preprint HAL n°01484099, Université Paris Descartes, 2017: [pdf].
- J. Ulloa, T. Aubin, D. Llusia, C. Bouveyron and J. Sueur, Measuring animal acoustic diversity in a tropical forest using unsupervised multiresolution analysis, Université Paris Descartes, 2016.
- C. Bouveyron, P. Latouche and P.-A. Mattei, Bayesian Variable Selection for Globally Sparse Probabilistic PCA, Preprint HAL n°01310409, Université Paris Descartes, 2016: [pdf].

Journal articles (30)

- C. Bouveyron, P. Latouche and R. Zreik, The Stochastic Topic Block Model for the Clustering of Networks with Textual Edges, Statistics and Computing, in press, 2017: [web] [pdf].
- C. Bouveyron, P. Latouche and R. Zreik, The Dynamic Random Subgraph Model for the Clustering of Evolving Networks, Computational Statistics, in press, 2017: [web] [pdf].
- C. Bouveyron, G. Hébrail, F.-X. Jollois and J.-M. Poggi, Un DU d’Analyste Big Data en formation continue courte, au niveau L3, Statistique et Enseignement, vol. 7 (1), pp. 127-134, 2016: [web].
- C. Bouveyron, J. Chiquet, P. Latouche and P.-A. Mattei, Combining a Relaxed EM Algorithm with Occam's Razor for Bayesian Variable Selection in High-Dimensional Regression, Journal of Multivariate Analysis, vol. 146, pp. 177-190, 2016: [web] [pdf].
- C. Bouveyron, M. Fauvel and S. Girard, Parsimonious Gaussian process models for the classification of hyperspectral remote sensing images, IEEE Geoscience and Remote Sensing Letters, vol. 12, pp.2423-2427, 2015: [web] [pdf].
- C. Bouveyron, E. Côme and J. Jacques, The discriminative functional mixture model for a comparative analysis of bike sharing systems, The Annals of Applied Statistics, vol. 9 (4), pp. 1726-1760, 2015: [web] [pdf].
- C. Bouveyron, P. Latouche and R. Zreik, Classification automatique de réseaux dynamiques avec sous-graphes : étude du scandale Enron, Journal de la Société Française de Statistique, vol.156(3), pp. 166-191, 2015: [web] [pdf].
- C. Bouveyron, M. Fauvel and S. Girard, Kernel discriminant analysis and clustering with parsimonious Gaussian process models, Statistics and Computing, vol. 25(6), pp. 1143-1162, 2015: [web] [pdf].
- C. Bouveyron, L. Jegou, Y. Jernite, S. Lamassé, P. Latouche & P. Rivera, The random subgraph model for the analysis of an ecclesiastical network in merovingian Gaul, The Annals of Applied Statistics, vol. 8(1), pp. 377-405, 2014: [web] [pdf].
- C. Bouveyron, Adaptive mixture discriminant analysis for supervised learning with unobserved classes, Journal of Classification, vol. 31(1), pp. 49-84, 2014: [web] [pdf].
- C. Bouveyron and C. Brunet, Model-based clustering of high-dimensional data: A review, Computational Statistics and Data Analysis, vol. 71, pp. 52-78, 2014: [web] [pdf].
- C. Bouveyron and J. Jacques, Adaptive mixtures of regressions: Improving predictive inference when population has changed, Communications in Statistics: Simulation and Computation, vol. 43(10), pp. 2570-2592, 2014: [web] [pdf].
- C. Bouveyron and C. Brunet, Discriminative variable selection for clustering with the sparse Fisher-EM algorithm, Computational Statistics, vol. 29(3-4), pp. 489-513, 2014: [web] [pdf].
- C. Bouveyron, Probabilistic model-based discriminant analysis and clustering methods in Chemometrics, Journal of Chemometrics, vol. 27(12), pp. 433-446, 2013: [web] [pdf].
- A. Bellas, C. Bouveyron, M. Cottrell & J. Lacaille, Model-based clustering of high-dimensional data streams with online mixture of probabilistic PCA, Advances in Data Analysis and Classification, vol. 7 (3), pp. 281-300, 2013: [web] [pdf].
- C. Bouveyron and C. Brunet, Theoretical and practical considerations on the convergence properties of the Fisher-EM algorithm, Journal of Multivariate Analysis, vol. 109, pp. 29-41, 2012: [web] [pdf].
- L. Bergé, C. Bouveyron and S. Girard, HDclassif: an R Package for Model-Based Clustering and Discriminant Analysis of High-Dimensional Data, Journal of Statistical Software, vol. 42 (6), pp. 1-29, 2012: [web] [pdf].
- C. Bouveyron and C. Brunet, Probabilistic Fisher discriminant analysis: A robust and flexible alternative to Fisher discriminant analysis, Neurocomputing, vol. 90 (1), pp. 12-22, 2012: [web] [pdf].
- C. Bouveyron and C. Brunet, Simultaneous model-based clustering and visualization in the Fisher discriminative subspace, Statistics and Computing, vol. 22 (1), pp. 301-324, 2012: [web] [pdf].
- C. Bouveyron and C. Brunet, On the estimation of the latent discriminative subspace in the Fisher-EM algorithm, Journal de la Société Française de Statistique, vol. 152 (3), pp. 98-115, 2011: [web] [pdf].
- C. Bouveyron, P. Gaubert and J. Jacques, Adaptive models in regression for modeling and understanding evolving populations, Journal of Case Studies in Business, Industry and Government Statistics, vol. 4 (2), pp. 83-92, 2011: [web] [pdf].
- C. Bouveyron, G. Celeux and S. Girard, Intrinsic Dimension Estimation by Maximum Likelihood in Isotropic Probabilistic PCA, Pattern Recognition Letters, vol. 32 (14), pp. 1706-1713, 2011: [web] [pdf].
- C.Bouveyron and J.Jacques, Model-based Clustering of Time Series in Group-specific Functional Subspaces, Advances in Data Analysis and Classification, vol. 5 (4), pp. 281-300, 2011: [web] [pdf].
- C. Bouveyron, O. Devos, L. Duponchel, S. Girard, J. Jacques & C. Ruckebusch, Gaussian mixture models for the classification of high-dimensional vibrational spectroscopy data, Journal of Chemometrics, vol. 24 (11-12), pp. 719-727, 2010: [web] [pdf].
- C. Bouveyron and J. Jacques, Adaptive linear models for regression: improving prediction when population has changed, Pattern Recognition Letters, vol. 31 (14), pp. 2237-2247, 2010: [web] [pdf].
- C. Bouveyron and S. Girard, Robust supervised classification with mixture models: Learning from data with uncertain labels, Pattern Recognition, vol. 42 (11), pp. 2649-2658, 2009 : [web] [pdf].
- C. Bouveyron and S. Girard, Classification supervisée et non supervisée des données de grande dimension, La revue Modulad, vol. 40, pp. 81-102, 2009 : [web] [pdf].
- C. Bouveyron, S. Girard and C. Schmid, High-Dimensional Data Clustering, Computational Statistics and Data Analysis, vol. 52 (1), pp. 502-519, 2007: [web] [pdf].
- C. Bouveyron, S. Girard and C. Schmid, High Dimensional Discriminant Analysis, Communications in Statistics: Theory and Methods, vol. 36 (14), pp. 2607-2623, 2007: [web].
- C. Bouveyron, S. Girard and C. Schmid, Class-Specific Subspace Discriminant Analysis for High-Dimensional Data, In Lecture Notes in Computer Science n°3940, pp. 139-150, Springer-Verlag, 2006: [web].

Book chapters (3)

- C. Bouveyron, Model-based clustering of high-dimensional data in Astrophysics, in Statistics for Astrophysics: Clustering and Classification, EAS Publications Series, EDP Sciencs, vol. 77, pp. 91-119, 2016: [web] [pdf].
- C. Bouveyron, C. Ducruet, P. Latouche and R. Zreik, Cluster Identification in Maritime Flows with Stochastic Methods, in Maritime Networks: Spatial Structures and Time Dynamics, Routledge, 2015: [web].
- F. Beninel, C. Biernacki, C. Bouveyron, J. Jacques and A. Lourme, Parametric link models for knowledge transfer in statistical learning, in Knowledge Transfer: Practices, Types and Challenges, Ed. Dragan Ilic, Nova Publishers, 2012: [web].

Editorials and discussions (5)

- C. Bouveyron and P. Latouche, Des réseaux, des textes et de la Statistique, La lettre de l'INSMI, CNRS, December, 2016: [web].
- C. Bouveyron, Apprentissage statistique en grande dimension : enjeux et avancées récentes, Journal de la Société Française de Statistique, vol. 155 (2), pp. 36-37, 2014: [web].
- C. Bouveyron, Discussion on the paper by J. Fan, Y. Liao and M. Mincheva, Journal of the Royal Statistical Society, Serie B, 2013.
- C. Bouveyron, Discussion on the paper by C. Hennig and T. Liao, Journal of the Royal Statistical Society, Serie C, 2013.
- C. Bouveyron, S. Girard and F. Forbes, Nouveaux défis en apprentissage statistique, Journal de la Société Française de Statistique, vol. 152 (3), pp. 1-2, 2011: [web].

Invited communications (12)

- C. Bouveyron, Model-based coclustering of functional data, Annual Conference of the Italian Statistical Society, Florence, Italy, June 2017.
- C. Bouveyron, Recent developments in model-based clustering of functional data, 22nd International Conference on Computational Statistics, Oviedo, Spain, August 2016.
- C. Bouveyron, Model-based clustering of functional data: application to the analysis of bike sharing systems, 12th International Conference on Operation Research, Havana, Cuba, March 2016.
- C. Bouveyron, Kernel discriminant analysis with parsimonious Gaussian process models,8th International Conference of the ERCIM WG on Computational and Methodological Statistics, London, UK, December 2015.
- C. Bouveyron, Discriminative clustering of high-dimensional data, Workshop on Model-Based Clustering and Classification, Catania, Italy, September 2014.
- C. Bouveyron, Discriminative variable selection for clustering, 6th International Conference of the ERCIM, WG on Computational and Methodological Statistics, London, UK, December 2013.
- C. Bouveyron, The random subgraph model for the analysis of an ecclesiastical network in merovingian Gaul, 20th Summer Working Group on Model-Based Clustering of the Department of Statistics of the University of Washington, Bologna, Italy, July 2013.
- C. Bouveyron, Clustering discriminatif et parcimonieux de données de grande dimension, Conférence du prix Simon Régnier, 19th meeting of the Société Francophone de Classification, Marseille, 2012.
- C. Bouveyron, Parsimonious and sparse Gaussian models for high-dimensional clustering, International Classification Conference 2011, St Andrews, UK, July 2011.
- C. Bouveyron, Model-based clustering of high-dimensional data: an overview and some recent advances, 17th Summer Working Group on Model-Based Clustering of the Department of Statistics of the University of Washington, Grenoble, France, July 2010.
- C. Bouveyron, Classification of complex data with model-based techniques, 1st joint meeting of the Statistical Society of Canada and the Société Française de Statistique, Ottawa, Canada, 2008.
- C. Bouveyron, An overview on high-dimensional data classification with model-based techniques, 8th International Conference on Operations Research, Havana, Cuba, 2008.


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