photo Matthieu Lerasle

Matthieu Lerasle

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Soumis


Publiés et Acceptés


  1. Non parametric estimation for random walks in random environment, with R. Diel, to appear in Stoch. Proc. Appl, (2017), arXiv:1606.03848.
  2. The number of potential winners in Bradley-Terry model in random environment, with R. Chetrite and R. Diel, Ann. Appl. Probab. 27, 3 (2017) 1372-1394 arXiv:1509.07265.
  3. Sub-Gaussian mean estimators, with L. Devroye, G. Lugosi and R. I. Oliveira, Ann. Statist. 44, 6 (2016) 2695--2725 arXiv:1509.05845.
  4. Family wise separation rates for multiple testing, with M. Fromont and P. Reynaud-Bouret, Ann. Statist., 44, 6 (2016) 2533-2563 hal-01107321v1.
  5. Parallel and pseudorandom discrete event system specification vs. networks of spiking neurons: Formalization and preliminary implementation results, with A. Muzy, F. Grammont, V.T. Dao and D.R.C. Hill, HPCS, Innsbruck, Austria, (2016).
  6. Optimal kernel selection for density estimation, with N. M. Magalhaes and P. Reynaud-Bouret, High dimensional probabilities VII: The Cargese Volume , volume 71 of Prog. Proba., Birkhauser (2016) 435--460 hal-01224097.
  7. Choice of V for V-fold cross-validation in least-squares density estimation, with S. Arlot, J. Mach. Learn. Res.; 17 (2016) (208):1--50, arXiv:1210.5830.
  8. Estimator Selection, Esaim Proc., 51 (2015) 232--245.
  9. Sharp oracle inequalities and slope heuristic for specification probabilities estimation in general random fields, with D.Y.Takahashi, Bernoulli, 22, 1 (2016) 325--344, arXiv:1106.2467.
  10. Markov approximation of chains of infinite order in the $\bar{d}$-metric, with S. Gallo and D.Y.Takahashi, Markov Process. Related Fields, 19 (2013) 51--82 arXiv:1107.4353.
  11. Kernels based tests with non-asymptotic bootstrap approaches for two-sample problem, with M. Fromont, B. Laurent and P. Reynaud-Bouret, JMLR W&CP, 23 (2012) 23.1--23.23.
  12. An Oracle Approach for Interaction Neighborhood Estimation in Random Field, with D. Y. Takahashi, Electron. J. Stat., 5 (2011) 534--571, arXiv:1010.4783.
  13. Optimal model selection in density estimation, Ann. Inst. Henri Poincarré, 48, 3 (2012) 884--908, arXiv:0910.1654.
  14. Optimal model selection for density estimation of stationary data under various mixing conditions, Ann. Statist, 39, 1 (2011) 1852--1877 , arXiv:0911.1497.
  15. Adaptive non-asymptotic confidence balls in density estimation, ESAIM P&S, 16 (2012) 61--85, arXiv:1007.4528.
  16. Adaptive density estimation for stationary processes, Math. Meth. Statist. 18, 1 (2009) 59--83, arXiv:0909.0999.

Non publiés