Anatoli Iouditski

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We discuss new methods for the recovery of signals with block-sparse structure, based on 1-minimization. Our emphasis is on the efficiently computable error bounds for the recovery routines. We optimize these bounds with respect to the method parameters to construct the estimators with improved statistical properties. We justify the proposed approach with(More)
We discuss two new methods of recovery of sparse signals from noisy observation based on ℓ 1-minimization. While they are closely related to the well-known techniques such as Lasso and Dantzig Selector, these estimators come with efficiently verifiable guaranties of performance. By optimizing these bounds with respect to the method parameters we are able to(More)
Prepared in the Verimag Laboratory within thé Ecole Doctorale Mathématiques, Sciences et Technologies de l'Information and under the supervision of Acknowledgements I am firstly grateful to the members of the jury, in particular to the reviewers , Mr Anders Rantzer and George Pappas. A lot of people contributed directly, indirectly, or in ways they could(More)
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