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20022015
most citedFast learning rates for plug-in classifiers

332 citations

Showing 2012 · math.STShow all

8 papers · 2 filters

math.ST20123 cited

Extended Itô calculus for symmetric Markov processes

Alexander Walsh

Chen, Fitzsimmons, Kuwae and Zhang (Ann. Probab. 36 (2008) 931-970) have established an Ito formula consisting in the development of F(u(X)) for a symmetric Markov process X, a fun…

math.ST2012231 cited

Needles and Straw in a Haystack: Posterior concentration for possibly sparse sequences

Ismaël Castillo, Aad van der Vaart

We consider full Bayesian inference in the multivariate normal mean model in the situation that the mean vector is sparse. The prior distribution on the vector of means is construc…

math.ST201212 cited

Kriging-based sequential design strategies using fast cross-validation techniques with extensions to multi-fidelity computer codes

Loic Le Gratiet, Claire Cannamela

Kriging-based surrogate models have become very popular during the last decades to approximate a computer code output from few simulations. In practical applications, it is very co…

math.ST20123 cited

Regularity dependence of the rate of convergence of the learning curve for Gaussian process regression

Loic Le Gratiet, Josselin Garnier

This paper deals with the speed of convergence of the learning curve in a Gaussian process regression framework. The learning curve describes the average generalization error of th…

math.ST2012

Thomas Bayes' walk on manifolds

Ismael Castillo, Gerard Kerkyacharian, Dominique Picard

Convergence of the Bayes posterior measure is considered in canonical statistical settings where observations sit on a geometrical object such as a compact manifold, or more genera…

math.ST2012

Blockwise SVD with error in the operator and application to blind deconvolution

S. Delattre, M. Hoffmann, D. Picard +1

We consider linear inverse problems in a nonparametric statistical framework. Both the signal and the operator are unknown and subject to error measurements. We establish minimax r…