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An accelerated proximal augmented Lagrangian method and its application in compressive sensing
As a first-order method, the augmented Lagrangian method (ALM) is a benchmark solver for linearly constrained convex programming, and in practice some semi-definite proximal terms are often added to its primal variable’s subproblem to make it more implementable. In this paper, we propose an accelera...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5651725/ https://www.ncbi.nlm.nih.gov/pubmed/29104401 http://dx.doi.org/10.1186/s13660-017-1539-0 |