Alternating Direction Method of Multipliers for Sparse and Low-Rank Decomposition Based on Nonconvex Nonsmooth Weighted Nuclear Norm

Alternating Direction Method of Multipliers for Sparse and Low-Rank Decomposition Based on Nonconvex Nonsmooth Weighted Nuclear Norm

Sparse and low-rank decomposition (SLRD) poses a big challenge in many fields. The existing methods are used to solve SLRD problem via formulating approximations of sparse and low-rank matrices. These conventional methods consider the approximation of the low-rank matrix as its nuclear norm, which i...

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Bibliographic Details
Main Authors: Zhenzhen Yang, Zhen Yang, Deren Han
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Sparse and low-rank decomposition
robust principal component analysis
alternating direction method of multipliers
nonconvex nonsmooth weighted nuclear norm
weighted singular value thresholding
Online Access:https://ieeexplore.ieee.org/document/8478175/

Internet

https://ieeexplore.ieee.org/document/8478175/

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