Journal
NEUROCOMPUTING
Volume 289, Issue -, Pages 1-12Publisher
ELSEVIER
DOI: 10.1016/j.neucom.2017.12.056
Keywords
Primal-dual method; Saddle-point problem; Nuclear norm; Total variation
Categories
Funding
- NNSF of China [11361018, 11461015]
- Guangxi Natural Science Foundation [2014GXNSFFA118001]
- Innovation Project of Guangxi and GUET Graduate Education [YJCXB201502]
- U.S. NSF [IIS-1423056, CMMI-1434401, CNS-1405985]
- NSF CAREER [IIS-1553687]
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We propose a simple primal-dual method for nuclear norm plus total variation minimization problems. A predictor-corrector scheme to the dual variable is used in our algorithm. Convergence of the method is proved and convergence rate which is O(1/N) in the ergodic sense is also discussed, where N denotes the iteration number. Numerical results including tensor completion, parallel magnetic resonance imaging and dynamic magnetic resonance imaging demonstrate the efficiency of the new algorithm. (C) 2018 Elsevier B.V. All rights reserved.
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