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Communication Dans Un Congrès Année : 2009

On statistical applications of l1-recovery

Résumé

We consider the problem of recovery of a sparse signal, observed the noisy environment when nuisance is present. We propose the recovery routines which are based on L1 minimization constrained or penalized with contrasts which depend on the geometry of the nuisance sets. We show that such routines outperform some known methods, e.g. Lasso estimator and Dantzig selector. We discuss the link between the theory of linear estimation and L1-recovery and show how this theory allows to construct optimal contrast matrices.
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Dates et versions

hal-00981928 , version 1 (23-04-2014)

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  • HAL Id : hal-00981928 , version 1

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Anatoli B. Juditsky, Fatma Kilinc Karzan, Arkadii S. Nemirovski. On statistical applications of l1-recovery. Workshop on Structure Adapting Methods, Nov 2009, Berlin, Germany. ⟨hal-00981928⟩
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