2 SELECT - Model selection in statistical learning
Inria Saclay - Ile de France, LMO - Laboratoire de Mathématiques d'Orsay, CNRS - Centre National de la Recherche Scientifique : UMR
Abstract : We provide a new algorithm for the treatment of the noisy inversion of the Radon transform using an appropriate thresholding technique adapted to a well-chosen new localized basis. We establish minimax results and prove their optimality. In particular, we prove that the procedures provided here are able to attain minimax bounds for any $\mathbb {L}_p$ loss. It s important to notice that most of the minimax bounds obtained here are new to our knowledge. It is also important to emphasize the adaptation properties of our procedures with respect to the regularity (sparsity) of the object to recover and to inhomogeneous smoothness. We perform a numerical study that is of importance since we especially have to discuss the cubature problems and propose an averaging procedure that is mostly in the spirit of the cycle spinning performed for periodic signals.
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Article dans une revue
Bernoulli, Bernoulli Society for Mathematical Statistics and Probability, 2012, 18 (2), pp.391-433. 〈10.3150/10-BEJ340〉
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https://hal.archives-ouvertes.fr/hal-00409903
Contributeur : Erwan Le Pennec <>
Soumis le : mardi 8 mai 2012 - 10:27:13
Dernière modification le : mercredi 21 mars 2018 - 18:56:49
Document(s) archivé(s) le : jeudi 9 août 2012 - 02:21:34

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### Citation

Gerard Kerkyacharian, Erwan Le Pennec, Dominique Picard. Radon needlet thresholding. Bernoulli, Bernoulli Society for Mathematical Statistics and Probability, 2012, 18 (2), pp.391-433. 〈10.3150/10-BEJ340〉. 〈hal-00409903v2〉

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