– T. Peel (LIF) : Matching Pursuit with Stochastic Selection

Carte non disponible

Date/heure
Date(s) - 13/09/2012
14 h 00 min - 15 h 00 min

Catégories Pas de Catégories


Matching pursuit with stochastic selection By Thomas Peel, LIF. We propose a Stochastic Selection strategy that ac- celerates the atom selection step of Matching Pursuit. This strategy consists of randomly selecting a subset of atoms and a subset of rows in the full dictionary at each step of the Matching Pursuit to obtain a sub-optimal but fast atom selection. We study the performance of the proposed algorithm in terms of approximation accuracy (decrease of the residual norm), of exact-sparse recovery and of audio declipping of real data. Numerical experiments show the relevance of the ap- proach. The proposed Stochastic Selection strategy is presented with Matching Pursuit but applies to any pursuit algorithms provided that their selection step is based on the computation of correlations.

– T. Peel (LIF) : Matching Pursuit with Stochastic Selection

Carte non disponible

Date/heure
Date(s) - 13/09/2012
14 h 00 min - 15 h 00 min

Catégories Pas de Catégories


Matching pursuit with stochastic selection\nBy Thomas Peel, LIF.\n\nWe propose a Stochastic Selection strategy that ac- celerates the atom selection step of Matching Pursuit. This strategy consists of randomly selecting a subset of atoms and a subset of rows in the full dictionary at each step of the Matching Pursuit to obtain a sub-optimal but fast atom selection. We study the performance of the proposed algorithm in terms of approximation accuracy (decrease of the residual norm), of exact-sparse recovery and of audio declipping of real data. Numerical experiments show the relevance of the ap- proach. The proposed Stochastic Selection strategy is presented with Matching Pursuit but applies to any pursuit algorithms provided that their selection step is based on the computation of correlations.[