Journal
IMA JOURNAL OF NUMERICAL ANALYSIS
Volume 35, Issue 1, Pages 394-426Publisher
OXFORD UNIV PRESS
DOI: 10.1093/imanum/drt060
Keywords
convex programming; separable structure; operator splitting methods; image processing
Categories
Funding
- NSFC [10971095, 91130007]
- MOEC fund [20110091110004]
- Hong Kong General Research Fund [HKBU 203311]
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We propose a splitting method for solving a separable convex minimization problem with linear constraints, where the objective function is expressed as the sum of m individual functions without coupled variables. Treating the functions in the objective separately, the new method belongs to the category of operator splitting methods. We show the global convergence and estimate a worst-case convergence rate for the new method, and then illustrate its numerical efficiency by some applications.
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