Algorithms for Sparsity-Constrained Optimization

This thesis demonstrates techniques that provide faster and more accurate solutions to a variety of problems in machine learning and signal processing. The author proposes a"greedy" algorithm, deriving sparse solutions with guarantees of optimality. The use of this algorithm removes many o...

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Detalles Bibliográficos
Autor principal: Bahmani, Sohail
Formato: Libro electrónico
Lenguaje:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2014.
Colección:Springer Theses, Recognizing Outstanding Ph.D. Research, 261
Materias:
Engineering.
Image processing.
Computer science > Mathematics.
Computer mathematics.
Signal, Image and Speech Processing.
Mathematical Applications in Computer Science.
Image Processing and Computer Vision.
Acceso en línea:http://dx.doi.org/10.1007/978-3-319-01881-2
Aporte de:Registro referencial: Solicitar el recurso aquí
Bibliotecas (ING-UNLP) de Universidad Nacional de La Plata

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