%0 Conference Proceedings
%T Region-based relaxations to accelerate greedy approaches
%+ Lab-STICC_ENSTAB_CID_PRASYS
%+ Institut de Recherche Mathématique de Rennes (IRMAR)
%+ SIMulation pARTiculaire de Modèles Stochastiques (SIMSMART)
%+ Lab-STICC_ENSTAB_CID_TOMS
%A Dorffer, Clément
%A Herzet, Cédric
%A Drémeau, Angélique
%< avec comité de lecture
%B 27th European Signal Processing Conference, EUSIPCO 2019
%C La Corogne, Spain
%8 2019-09-02
%D 2019
%R 10.23919/EUSIPCO.2019.8902669
%K Sparse approximation
%K atom selection
%K low-complexity methods
%Z Engineering Sciences [physics]/Signal and Image processing
%Z Mathematics [math]/Optimization and Control [math.OC]
%Z Statistics [stat]/Machine Learning [stat.ML]Conference papers
%X We propose a low-computational strategy for the efficient implementation of the "atom selection step" in sparse representation algorithms. The proposed procedure is based on simple tests enabling to identify subsets of atoms which cannot be selected. Our procedure applies on both discrete or continuous dictionaries. Experiments performed on the standard "Gaussian deconvolution" problem show the computational gain induced by the proposed approach.
%G English
%2 https://inria.hal.science/hal-02059649/document
%2 https://inria.hal.science/hal-02059649/file/eusipco_DHD.pdf
%L hal-02059649
%U https://inria.hal.science/hal-02059649
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