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Bibliography

Major publications by the team in recent years
  • 1J.-Y. Audibert, O. Catoni.
    Robust linear least squares regression, in: The Annals of Statistics, 2011, vol. 39, no 5, pp. 2766-2794.
    http://hal.inria.fr/hal-00522534
  • 2K. Bertin, E. Le Pennec, V. Rivoirard.
    Adaptive Dantzig density estimation, in: Annales de l'IHP, Probabilités et Statistiques, 2011, vol. 47, no 1, pp. 43–74.
    http://hal.inria.fr/hal-00381984/en
  • 3G. Biau, L. Devroye, G. Lugosi.
    Consistency of random forests and other averaging classifiers, in: Journal of Machine Learning Research, 2008, vol. 9, pp. 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, pp. 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 p.
    http://dx.doi.org/10.1214/074921707000000391
  • 7O. Catoni.
    Challenging the empirical mean and empirical variance: A deviation study, in: Annales de l'Institut Henri Poincaré - Probabilités et Statistiques, 2012, vol. 48, no 4, pp. 1148-1185.
  • 8M. 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.
  • 9G. Lugosi, S. Mannor, G. Stoltz.
    Strategies for prediction under imperfect monitoring, in: Mathematics of Operations Research, 2008, vol. 33, pp. 513–528.
  • 10B. Mauricette, V. Mallet, G. Stoltz.
    Ozone ensemble forecast with machine learning algorithms, in: Journal of Geophysical Research, 2009, vol. 114.
    http://dx.doi.org/10.1029/2008JD009978
  • 11V. Rivoirard, G. Stoltz.
    Statistique mathématique en action, second edition, Vuibert, 2012.
    http://www.dma.ens.fr/statenaction/
Publications of the year

Articles in International Peer-Reviewed Journals

  • 12P. Alquier, G. Biau.
    Sparse single-index model, in: Journal of Machine Learning Research, 2013, vol. 14, pp. 243–280.
    http://hal.inria.fr/hal-00556652
  • 13O. Cappé, A. Garivier, O.-A. Maillard, R. Munos, G. Stoltz.
    Kullback-Leibler Upper Confidence Bounds for Optimal Sequential Allocation, in: Annals of Statistics, 2013, vol. 41, no 3, pp. 1516-1541, Accepted.
    http://hal.inria.fr/hal-00738209
  • 14M. Devaine, P. Gaillard, Y. Goude, G. Stoltz.
    Forecasting electricity consumption by aggregating specialized experts, in: Machine Learning, 2013, vol. 90, no 2, pp. 231-260.
    http://hal.inria.fr/hal-00484940
  • 15S. Mannor, V. Perchet, G. Stoltz.
    A Primal Condition for Approachability with Partial Monitoring, in: Journal of Dynamics and Games, 2013, in press.
    http://hal.inria.fr/hal-00772056
  • 16T. Michalski, G. Stoltz.
    Do countries falsify economic data strategically? Some evidence that they might., in: The Review of Economics and Statistics, May 2013, vol. 95, no 2, pp. 591-616. [ DOI : 10.1162/REST_a_00274 ]
    http://hal.inria.fr/halshs-00482106

Other Publications


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