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Bibliography

Publications of the year

Doctoral Dissertations and Habilitation Theses

  • 1S. Fu.

    Inversion probabiliste bayésienne en analyse d'incertitude, Université Paris-sud 11, 2012.
  • 2C. Meynet.

    Sélection de variables pour la classification non supervisée en grande dimension, Université Paris-sud 11, 2012.

Articles in International Peer-Reviewed Journals

  • 3M. Aminghafari, J.-M. Poggi.

    Multistep Forecasting Non-Stationary Time Series using Wavelets and Kernel Smoothing, in: Communications in Statistics-Theory and Methods, 2012, vol. 41, no 3, p. 485–499.
  • 4A. Antoniadis, X. Brossat, J. Cugliari, J.-M. Poggi.

    Functional Clustering using Wavelets, in: International Journal of Wavelets, Multiresolution and Information Processing, 2012, Accepted for publication.
  • 5J.-P. Baudry, C. Maugis, B. Michel.

    Slope heuristics: overview and implementation, in: Statistics and Computing, 2012, vol. 22, no 2, p. 455-470. [ DOI : 10.1007/s11222-011-9236-1 ]

    http://hal.inria.fr/hal-00666838
  • 6S. X. Cohen, E. Le Pennec.

    Partition-Based Conditional Density Estimation, in: ESAIM: Probability and Statistics, 2012. [ DOI : 10.1051/ps/2012017 ]

    http://hal.inria.fr/hal-00752943
  • 7G. Kerkyacharian, E. Le Pennec, D. Picard.

    Radon needlet thresholding, in: Bernoulli, 2012, vol. 18, no 2, p. 391-433. [ DOI : 10.3150/10-BEJ340 ]

    http://hal.inria.fr/hal-00409903
  • 8P. Massart, C. Meynet.

    Around Nemirovski’s inequality, in: IMS collections, 2012, vol. 9, p. 254–265.
  • 9A. Saumard.

    Optimal upper and lower bounds for the true and empirical excess risks in heteroscedastic least-squares regression, in: Electron. J. Statist., 2012, vol. 6, no 1-2, p. 579–655.
  • 10T. Van Erven, M. Reid, R. Williamson.

    Mixability is Bayes Risk Curvature Relative to Log Loss, in: Journal of Machine Learning Research, special issue on Inductive Logic Programming, May 2012, no 13, p. 1639–1663.

    http://hal.inria.fr/hal-00758204
  • 11V. 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, 2012, to appear.

Articles in National Peer-Reviewed Journals

  • 12A. Antoniadis, X. Brossat, J. Cugliari, J.-M. Poggi.

    Prévision d’un processus à valeurs fonctionnelles en présence de non stationnarités. Application à la consommation d’électricité, in: Journal de la Société Française de Statistique, 2012, Accepted for publication.

International Conferences with Proceedings

  • 13V. Brault, J.-P. Baudry, C. Maugis-Rabusseau, B. Michel.

    Package Capushe pour le logiciel R, in: 44ème journées de statistique, Université libre de Bruxelles, campus du Solbosch, 05 2012.

    http://jds2012.ulb.ac.be/myreview/files/default/submission/submission_184.pdf
  • 14V. Brault, J.-P. Baudry, C. Maugis-Rabusseau, B. Michel.

    Package Capushe pour le logiciel R, in: 1ère Rencontres R, Université de Bordeaux, campus Victoire, 07 2012.

    http://hal.archives-ouvertes.fr/hal-00717565
  • 15V. Brault, G. Celeux, C. Keribin.

    Régularisation bayésienne du modèle des blocs latents, in: 44ème journées de statistique, Université libre de Bruxelles, campus du Solbosch, 05 2012.

    http://jds2012.ulb.ac.be/myreview/files/default/submission/submission_126.pdf
  • 16V. Brault, G. Celeux, C. Keribin.

    Régularisation bayésienne du modèle des blocs latents, in: Workshop ClasSel, IHP, 11 rue Pierre et Marie Curie - 75231 Paris, 01 2012.

    https://sites.google.com/site/workshopclassel/resumes
  • 17V. Brault, G. Celeux, C. Keribin.

    Régularisation bayésienne du modèle des blocs latents, in: 44èmes Journées de Statistique, Bruxelles, France, 2012.

    http://jds2012.ulb.ac.be/myreview/files/default/submission/submission_126.pdf
  • 18R. Fourchereau, G. Celeux, P. Pamphile.

    Probabilistic modelling of SN curve, in: S2MRSA, Bordeaux, France, July 4-6th 2012.
  • 19C. Keribin, V. Brault, G. Celeux, G. Govaert.

    Model selection for the binary latent block model, in: 20th International Conference on Computational Statistics (COMPSTAT 2012, Limassol, Cyprus, August 2012.
  • 20P. Massart, C. Meynet.

    Some Rates of Convergence for the Selected Lasso Estimator, in: 23rd International Conference Algorithmic Learning Theory 2012, Lyon, France, Springer Berlin/Heidelberg, October 29-31 2012, p. 17–33, Algorithmic Learning Theory.
  • 21F. Mhamdi, M. Jaidane, J.-M. Poggi.

    Forecasting time series through reconstructed multiple seasonal patterns using Empirical Mode Decomposition, in: Proceedings of the 20th International Conference on Computational Statistics COMPSTAT2012, Limassol, Cyprus, 2012, p. 573–583.
  • 22T. Van Erven, P. Grünwald, M. Reid, R. Williamson.

    Mixability in Statistical Learning, in: Advances in Neural Information Processing Systems 25 (NIPS 2012), Lake Tahoe, United States, December 2012.

National Conferences with Proceeding

  • 23R. Fourchereau, G. Celeux, P. Pamphile.

    Modélisation Statistique des données de fatigue matériau, in: Actes du congrès lambdamu18-IMDR, 2012.

Conferences without Proceedings

  • 24A. Antoniadis, X. Brossat, J. Cugliari, J.-M. Poggi.

    Clustering functional data using wavelets, in: 8th World Congress Proba & Stat, Istanbul, 2012.
  • 25A. Antoniadis, X. Brossat, J. Cugliari, J.-M. Poggi.

    Non parametric forecasting of a function-valued non stationary processes. Application to the electricity demand, in: 5th International Conference of the ERCIM Working Group on Computing and Statistics, Oviedo, Spain, 2012.
  • 26M. Misiti, Y. Misiti, J.-M. Poggi, B. Portier.

    PM10 forecasting using mixture linear regression models, in: 46th scientific meeting of the Italian Statistical Society, SIS 2012, Rome, 2012.
  • 27M. Misiti, Y. Misiti, J.-M. Poggi, B. Portier.

    PM10 forecasting using mixture linear regression models, in: ENBIS 2012, Ljubana, 2012.

Internal Reports

  • 28A. Antoniadis, X. Brossat, J. Cugliari, J.-M. Poggi.

    Prévision d'un processus à valeurs fonctionnelles en présence de non stationnarités. Application à la consommation d'électricité., Inria, June 2012, no RR-7982.

    http://hal.inria.fr/hal-00703570
  • 29J.-P. Baudry, M. Cardoso, G. Celeux, M.-J. Amorim, A. Sousa Ferreira.

    Enhancing the selection of a model-based clustering with external qualitative variables, Inria, October 2012, no RR-8124, 14 p.

    http://hal.inria.fr/hal-00747387
  • 30S. Fu, G. Celeux, N. Bousquet, M. Couplet.

    Bayesian inference for inverse problems occurring in uncertainty analysis, Inria, June 2012, no RR-7995.

    http://hal.inria.fr/hal-00708814

Other Publications

  • 31J.-P. Baudry, M. Cardoso, G. Celeux, M.-J. Amorim, A. Sousa Ferreira.

    Enhancing the selection of a model-based clustering with external qualitative variables, 2012, HAL.

    http://hal.inria.fr/hal-00747854
  • 32V. Brault, G. Celeux, G. Govaert, C. Keribin.

    Estimation and Selection for the Latent Block Model on nominal data, 2012.
  • 33S. X. Cohen, E. Le Pennec.

    Conditional Density Estimation by Penalized Likelihood Model Selection, 2012, Submitted.
  • 34C. Meynet, C. Maugis-Rabusseau.

    A sparse variable selection procedure in model-based clustering, June 2012, HAL.

    http://hal.inria.fr/hal-00734316
  • 35M. Misiti, Y. Misiti, J.-M. Poggi, B. Portier.

    Mixture of linear regression models for short term PM10 forecasting in Haute Normandie (France), 2012, Submitted.
  • 36T. Van Erven, P. Harremoës.

    Rényi Divergence and Kullback-Leibler Divergence, 2012, Submitted to IEEE Transactions on Information Theory.

    http://hal.inria.fr/hal-00758191


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