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Region-based relaxations to accelerate greedy approaches

Clément Dorffer 1 Cédric Herzet 2, 3 Angélique Drémeau 4
1 Lab-STICC_ENSTAB_CID_PRASYS
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
4 Lab-STICC_ENSTAB_CID_TOMS
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
Abstract : 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.
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https://hal.inria.fr/hal-02059649
Contributor : Cédric Herzet <>
Submitted on : Wednesday, March 6, 2019 - 6:08:22 PM
Last modification on : Wednesday, April 21, 2021 - 11:18:10 AM
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Clément Dorffer, Cédric Herzet, Angélique Drémeau. Region-based relaxations to accelerate greedy approaches. 27th European Signal Processing Conference, EUSIPCO 2019, Sep 2019, La Corogne, Spain. ⟨hal-02059649⟩

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