Major publications by the team in recent years
  • 1J.-Y. Audibert, O. Catoni.

    Robust linear least squares regression, in: The Annals of Statistics, 2011, in press.

  • 2K. Bertin, E. Le Pennec, V. Rivoirard.

    Adaptive Dantzig density estimation, in: Annales de l'IHP, Probabilités et Statistiques, 2011, vol. 47, no 1, p. 43–74.

  • 3G. Biau, L. Devroye, G. Lugosi.

    Consistency of random forests and other averaging classifiers, in: Journal of Machine Learning Research, 2008, vol. 9, p. 2015–2033.
  • 4G. Biau, L. Devroye, G. Lugosi.

    On the performance of clustering in Hilbert spaces, in: IEEE Transactions on Information Theory, 2008, vol. 54, p. 781–790.
  • 5O. Catoni.

    Statistical Learning Theory and Stochastic Optimization — Lectures on Probability Theory and Statistics, École d'Été de Probabilités de Saint-Flour XXXI – 2001, Lecture Notes in Mathematics, Springer, 2004, vol. 1851, 269 pages.
  • 6O. Catoni.

    PAC-Bayesian Supervised Classification: The Thermodynamics of Statistical Learning, IMS Lecture Notes Monograph Series, Institute of Mathematical Statistics, 2007, vol. 56, 163 pages.

  • 7M. Devaine, P. Gaillard, Y. Goude, G. Stoltz.

    Forecasting electricity consumption by aggregating specialized experts; a review of the sequential aggregation of specialized experts, with an application to Slovakian and French country-wide one-day-ahead (half-)hourly predictions, in: Machine Learning, 2012, to appear.
  • 8G. Lugosi, S. Mannor, G. Stoltz.

    Strategies for prediction under imperfect monitoring, in: Mathematics of Operations Research, 2008, vol. 33, p. 513–528.
  • 9B. Mauricette, V. Mallet, G. Stoltz.

    Ozone ensemble forecast with machine learning algorithms, in: Journal of Geophysical Research, 2009, vol. 114, D05307 p.

  • 10V. Rivoirard, G. Stoltz.

    Statistique mathématique en action, second edition, Vuibert, 2012.

Publications of the year

Articles in International Peer-Reviewed Journals

  • 11G. Biau.

    Analysis of a random forests model, in: Journal of Machine Learning Research, 2012, vol. 13, p. 1063–1095.

  • 12G. Biau, L. Devroye, V. Dujmović, A. Krzyżak.

    An affine invariant k-nearest neighbor regression estimate, in: Journal of Multivariate Analysis, 2012, vol. 112, p. 24–34.

  • 13G. Biau, A. Fischer.

    Parameter selection for principal curves, in: IEEE Transactions on Information Theory, 2012, vol. 58, p. 1924–1939.

  • 14G. Biau, A. Mas.

    PCA-kernel estimation, statistics & risk modeling, in: Statistics & Risk Modeling, 2012, vol. 29, p. 19–46.

  • 15G. Biau, Y. G. Yatracos.

    On the shrinkage estimation of variance and Pitman closeness criterion, in: Journal de la Société Française de Statistique, 2012, vol. 153, p. 5–21.

  • 16O. Catoni.

    Challenging the empirical mean and empirical variance: a deviation study, in: Ann. Inst. Henri Poincaré, 2012, vol. 48, no 4, p. 1148-1185.

  • 17M. Devaine, P. Gaillard, Y. Goude, G. Stoltz.

    Forecasting electricity consumption by aggregating specialized experts, in: Machine Learning, 2012, to appear.

  • 18M. Doumic-Jauffret, M. Hoffmann, P. Reynaud-Bouret, V. Rivoirard.

    Nonparametric estimation of the division rate of a size-structured population, in: SIAM Journal on Numerical Analysis, 2012, vol. 50, no 2, p. 925–950.

  • 19S. Gerchinovitz.

    Sparsity regret bounds for individual sequences in online linear regression, in: Journal of Machine Learning Research, 2012, to appear.

  • 20S. Gerchinovitz, J. Y. Yu.

    Adaptive and optimal online linear regression on L1-balls, in: Theoretical Computer Science, 2012, to appear.

  • 21P. Ngoc, T. Mai, V. Rivoirard.

    The dictionary approach for spherical deconvolution, in: Journal of Multivariate Analysis, 2012, to appear.

  • 22V. Rivoirard, J. Rousseau.

    Bernstein-von Mises theorem for linear functionals of the density, in: The Annals of Statistics, 2012, vol. 40, no 3, p. 1489–1523.

  • 23V. Rivoirard, J. Rousseau.

    Posterior concentration rates for infinite dimensional exponential families, in: Bayesian Analysis, 2012, vol. 7, no 2, p. 311–333.


International Conferences with Proceedings

  • 24N. Cesa-Bianchi, P. Gaillard, G. Lugosi, G. Stoltz.

    Mirror descent meets fixed share (and feels no regret), in: Advances in Neural Information Processing Systems (NIPS), Lake Tahoe, United States, December 2012, vol. 25, Paper 471 p.


Scientific Books (or Scientific Book chapters)

Books or Proceedings Editing

Internal Reports

  • 27C.-P. Astolfi, S. Da Veiga, G. Stoltz.

    Forecasting production data of oil reservoirs with experts, IFP Energies nouvelles, 2012, 68 pages.

Other Publications