Result: Exact optimization for the ℓ1-Compressive Sensing problem using a modified Dantzig―Wolfe method
Title:
Exact optimization for the ℓ1-Compressive Sensing problem using a modified Dantzig―Wolfe method
Authors:
Source:
Theoretical Computer Science Issues in Image Analysis and ProcessingTheoretical computer science. 412(15):1325-1337
Publisher Information:
Oxford: Elsevier, 2011.
Publication Year:
2011
Physical Description:
print, 52 ref
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences et techniques communes, Sciences and techniques of general use, Mathematiques, Mathematics, Analyse mathématique, Mathematical analysis, Calcul des variations et contrôle optimal, Calculus of variations and optimal control, Analyse numérique. Calcul scientifique, Numerical analysis. Scientific computation, Analyse numérique, Numerical analysis, Méthodes numériques en programmation mathématique, optimisation et calcul variationnel, Numerical methods in mathematical programming, optimization and calculus of variations, Optimisation et calcul variationnel numériques, Numerical methods in optimization and calculus of variations, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Informatique théorique, Theoretical computing, Algorithmique. Calculabilité. Arithmétique ordinateur, Algorithmics. Computability. Computer arithmetics, Divers, Miscellaneous, Algorithme, Algorithm, Algoritmo, Informatique théorique, Computer theory, Informática teórica, Méthode décomposition, Decomposition method, Método descomposición, Méthode optimisation, Optimization method, Método optimización, Optimisation, Optimization, Optimización, Programmation linéaire, Linear programming, Programación lineal, Résultat expérimental, Experimental result, Resultado experimental, Solution exacte, Exact solution, Solución exacta, 49XX, 65K10, 65Kxx, 68Wxx, Méthode linéaire, Méthode modifiée, Compressed sensing, Pivoting rules
Document Type:
Academic journal
Article
File Description:
text
Language:
English
Author Affiliations:
Univ Paris-Sud, UMR8623, LRI, Orsay, 91405, France
CMIA, ENS Cachan, CNRS, PRES UniverSud, 94230, France
CMIA, ENS Cachan, CNRS, PRES UniverSud, 94230, France
ISSN:
0304-3975
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Mathematics
Mathematics
Accession Number:
edscal.23943795
Database:
PASCAL Archive
Further Information
This paper considers the l1-Compressive Sensing problem and presents an efficient algorithm that computes an exact solution. The idea consists in reformulating the problem such that it yields a modified Dantzig-Wolfe decomposition that allows to efficiently apply all standard simplex pivoting rules. Experimental results show the superiority of our approach compared to standard linear programming methods.