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Adaptive singular value thresholding

Zarmehi, N ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1109/SAMPTA.2017.8024355
  3. Abstract:
  4. In this paper, we propose an Adaptive Singular Value Thresholding (ASVT) for low rank recovery under affine constraints. Unlike previous iterative methods that the threshold level is independent of the iteration number, in our proposed method, the threshold in adaptively decreases during iterations. The simulation results reveal that we get better performance with this thresholding strategy. © 2017 IEEE
  5. Keywords:
  6. Affine constraints ; Iteration numbers ; Low-rank recoveries ; Singular values ; Threshold levels ; Thresholding ; Iterative methods
  7. Source: 2017 12th International Conference on Sampling Theory and Applications, SampTA 2017, 3 July 2017 through 7 July 2017 ; 2017 , Pages 442-445 ; 9781538615652 (ISBN)
  8. URL: https://ieeexplore.ieee.org/document/8024355