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Communication Dans Un Congrès Année : 2013

A new algorithm for learning overcomplete dictionaries

Résumé

In this paper, we propose a new algorithm for learning overcomplete dictionaries. The proposed algorithm is actually a new approach for optimizing a recently proposed cost function for dictionary learning. This cost function is regularized with a term that encourages low similarity between different atoms. While the previous approach needs to run an iterative limited-memory BFGS (l-BFGS) algorithm at each iteration of another iterative algorithm, our approach uses a closedform formula. Experimental results on reconstruction of a true underlying dictionary and designing a sparsifying dictionary for a class of autoregressive signals show that our approach results in both better quality and lower computational load.
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Dates et versions

hal-00867093 , version 1 (27-09-2013)

Identifiants

  • HAL Id : hal-00867093 , version 1

Citer

Mostafa Sadeghi, Massoud Babaie-Zadeh, Christian Jutten. A new algorithm for learning overcomplete dictionaries. EUSIPCO 2013 - 21th European Signal Processing Conference, Sep 2013, Marrakech, Morocco. pp.EUSIPCO 2013 1569746047. ⟨hal-00867093⟩
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