%0 Conference Paper
%F Oral 
%T Efficient atom selection strategy for iterative sparse approximations
%+ Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC)
%+ Lab-STICC_ENSTAB_CID_TOMS
%+ Institut de Recherche Mathématique de Rennes (IRMAR)
%+ Inria Rennes – Bretagne Atlantique 
%A Dorffer, Clément
%A Drémeau, Angélique
%A Herzet, Cédric
%< avec comité de lecture
%B iTWIST 2018 - International Traveling Workshop on Interactions between low-complexity data models and Sensing Techniques
%C Marseille, France
%P 1-3
%8 2018-11-21
%D 2018
%Z Engineering Sciences [physics]/Signal and Image processing
%Z Statistics [stat]/Machine Learning [stat.ML]
%Z Mathematics [math]/Optimization and Control [math.OC]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 DOA and Gaussian deconvolution problems show the computational gain induced by the proposed approach.
%G English
%2 https://inria.hal.science/hal-01937501/document
%2 https://inria.hal.science/hal-01937501/file/main_v5_Cedric_edit.pdf
%L hal-01937501
%U https://inria.hal.science/hal-01937501
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