Publications of the year

Doctoral Dissertations and Habilitation Theses

  • 1E. Le Pennec.

    Some (statistical) applications of Ockham's principle, Université Paris Sud - Paris XI, March 2013, Habilitation à Diriger des Recherches.


Articles in International Peer-Reviewed Journals

  • 2S. X. Cohen, E. Le Pennec.

    Partition-Based Conditional Density Estimation, in: ESAIM: Probability and Statistics, 2013, vol. 17, pp. 672–697. [ DOI : 10.1051/ps/2012017 ]

  • 3M. Gallopin, A. Rau, F. Jaffrézic.

    A Hierarchical Poisson Log-Normal Model for Network Inference from RNA Sequencing Data, in: PLoS ONE, October 2013.

  • 4A. Rau, M. Gallopin, G. Celeux, F. Jaffrezic.

    Data-based filtering for replicated high-throughput transcriptome sequencing experiments, in: Bioinformatics, 2013, vol. 29, pp. 2146-2152. [ DOI : 10.1093/bioinformatics/btt350 ]

  • 5V. Vandewalle, C. Biernacki, G. Celeux, G. Govaert.

    A predictive deviance criterion for selecting a generative model in semi-supervised classification, in: Computational Statistics and Data Analysis, 2013, vol. 64, pp. 220-236.


Invited Conferences

  • 6G. Celeux.

    How useful Bayesian inference could be in Model-based clustering?, in: Advances in Latent Variables-Methods, Models and Applications, Brescia, Italy, Società italiana di statistica, June 2013.

  • 7G. Celeux.

    The notion of alpha-admissible models: illustrations in the model-based clustering context, in: Working Group on Model-Based Clustering, Bologne, Italy, University of Bologna, July 2013.

  • 8G. Celeux.

    Variable selection in clustering and classification: issues, difficulties and solutions, in: AG DANK/BCS Meeting 2013, London, United Kingdom, C. Hennig (editor), German and British Classification Societies, November 2013.


International Conferences with Proceedings

  • 9L. Montuelle, E. Le Pennec.

    R égression gaussienne à poids logistiques et maximum de vraisemblance p énalis é, in: JDS-45e Journées de Statistique, Toulouse, France, May 2013.


Conferences without Proceedings

  • 10V. Brault.

    Modèle des blocs latents et algorithme Largest Gaps, in: Cinquièmes Rencontres des Jeunes Statisticien-ne-s, Aussois, France, Jérôme Saracco, August 2013.

  • 11V. Brault, G. Celeux, C. Keribin.

    Comparaisons de différents algorithmes pour le modèle des blocs latents, in: Séminaire AgroSelect, Paris, France, October 2013.

  • 12M. Gallopin.

    Gene network inference from miRNA-seq data, in: MicroRNA Workshop "MicroRNA Technology, Relevance and Application", Bruxelles, Belgium, May 2013.

  • 13M. Gallopin.

    Inferring gene networks from RNA-seq data, in: 5th workshop statseq, Helsinki, Finland, April 2013.

  • 14C. Keribin, V. Brault.

    Model selection with untractable likelihood, in: ERCIM - 6th International Conference of the ERCIM Working Group on Computing and Statistics, 2013, London, United Kingdom, December 2013.


Internal Reports

  • 15C. Keribin, V. Brault, G. Celeux, G. Govaert.

    Estimation and Selection for the Latent Block Model on Categorical Data, Inria, March 2013, no RR-8264, 31 p.

  • 16M. Misiti, Y. Misiti, J.-M. Poggi, B. Portier.

    Mixture of linear regression models for short term PM10 forecasting in Haute Normandie (France), February 2013.

  • 17L. Montuelle, E. Le Pennec, S. Cohen.

    Gaussian Mixture Regression model with logistic weights, a penalized maximum likelihood approach, Inria, April 2013, no RR-8281.


Other Publications

  • 18A. Antoniadis, X. Brosat, J. Cugliari, J.-M. Poggi.

    Une approche fonctionnelle pour la prévision non-paramétrique de la consommation d'électricité, 2013, 1 p.

  • 19G. Celeux, M.-L. Martin-Magniette, C. Maugis-Rabusseau, A. E. Raftery.

    Comparing Model Selection and Regularization Approaches to Variable Selection in Model-Based Clustering, 2013.

  • 20J. Cugliari.

    Conditional Autoregressive Hilbertian processes, 2013.

  • 21R. Fouchereau, G. Celeux, P. Pamphile.

    Probabilistic modeling of S-N curves, January 2014.

  • 22C. Levrard.

    Margin conditions for vector quantization, 2013, 42 p.

  • 23C. Levrard.

    Non Asymptotic Bounds for Vector Quantization, 2013, 27 p, Technical proofs are omitted and can be found in the related unpublished paper "Margin conditions for vector quantization".

  • 24L. Rémi, I. Serge, L. Florent, C. Biernacki, G. Celeux, G. Govaert.

    Rmixmod: The R Package of the Model-Based Unsupervised, Supervised and Semi-Supervised Classification Mixmod Library, 2013.

  • 25A. Saumard.

    Optimal model selection in heteroscedastic regression using piecewise polynomials, 2013.

  • 26T. Van Erven, J. Cugliari.

    Game-theoretically Optimal Reconciliation of Contemporaneous Hierarchical Time Series Forecasts, December 2013.

  • 27S. de Rooij, T. Van Erven, P. Grünwald, W. Koolen.

    Follow the Leader If You Can, Hedge If You Must, December 2013.