Bibliography

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.
  http://hal.inria.fr/tel-00802653

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 ]
  http://hal.inria.fr/hal-00915854
• 3M. Gallopin, A. Rau, F. Jaffrézic.
  A Hierarchical Poisson Log-Normal Model for Network Inference from RNA Sequencing Data, in: PLoS ONE, October 2013.
  http://hal.inria.fr/hal-00921397
• 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 ]
  http://hal.inria.fr/hal-00927025
• 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.
  http://hal.inria.fr/inria-00516991

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.
  http://hal.inria.fr/hal-00927006
• 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.
  http://hal.inria.fr/hal-00926997
• 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.
  http://hal.inria.fr/hal-00927011

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.
  http://hal.inria.fr/hal-00921524

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.
  http://hal.inria.fr/hal-00924395
• 11V. Brault, G. Celeux, C. Keribin.
  Comparaisons de différents algorithmes pour le modèle des blocs latents, in: Séminaire AgroSelect, Paris, France, October 2013.
  http://hal.inria.fr/hal-00924404
• 12M. Gallopin.
  Gene network inference from miRNA-seq data, in: MicroRNA Workshop "MicroRNA Technology, Relevance and Application", Bruxelles, Belgium, May 2013.
  http://hal.inria.fr/hal-00921413
• 13M. Gallopin.
  Inferring gene networks from RNA-seq data, in: 5th workshop statseq, Helsinki, Finland, April 2013.
  http://hal.inria.fr/hal-00921449
• 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.
  http://hal.inria.fr/hal-00924197

Internal Reports

• 15C. Keribin, V. Brault, G. Celeux, G. Govaert.
  Estimation and Selection for the Latent Block Model on Categorical Data, Inria, March 2013, n^o RR-8264, 31 p.
  http://hal.inria.fr/hal-00802764
• 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.
  http://hal.inria.fr/hal-00841349
• 17L. Montuelle, E. Le Pennec, S. Cohen.
  Gaussian Mixture Regression model with logistic weights, a penalized maximum likelihood approach, Inria, April 2013, n^o RR-8281.
  http://hal.inria.fr/hal-00809735

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.
  http://hal.inria.fr/hal-00814530
• 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.
  http://hal.inria.fr/hal-00849439
• 20J. Cugliari.
  Conditional Autoregressive Hilbertian processes, 2013.
  http://hal.inria.fr/hal-00788249
• 21R. Fouchereau, G. Celeux, P. Pamphile.
  Probabilistic modeling of S-N curves, January 2014.
  http://hal.inria.fr/hal-00924080
• 22C. Levrard.
  Margin conditions for vector quantization, 2013, 42 p.
  http://hal.inria.fr/hal-00877093
• 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".
  http://hal.inria.fr/hal-00877564
• 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.
  http://hal.inria.fr/hal-00919486
• 25A. Saumard.
  Optimal model selection in heteroscedastic regression using piecewise polynomials, 2013.
  http://hal.inria.fr/hal-00512306
• 26T. Van Erven, J. Cugliari.
  Game-theoretically Optimal Reconciliation of Contemporaneous Hierarchical Time Series Forecasts, December 2013.
  http://hal.inria.fr/hal-00920559
• 27S. de Rooij, T. Van Erven, P. Grünwald, W. Koolen.
  Follow the Leader If You Can, Hedge If You Must, December 2013.
  http://hal.inria.fr/hal-00920549