Results 21 to 30 of about 1,952,092 (277)
Dynamic MRI Reconstruction Combining Tensor Nuclear Norm and Casorati Matrix Nuclear Norm [PDF]
, 2022 Low-rank tensor models have been applied in accelerating dynamic magnetic resonance imaging (dMRI). Recently, a new tensor nuclear norm based on t-SVD has been proposed and applied to tensor completion.
Hu, Yue, Lu, Xin, Zhang, Yinghao
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Norm-Attaining Tensors and Nuclear Operators [PDF]
Mediterranean Journal of Mathematics, 2022 25 pages.
Sheldon Dantas +3 more
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Nuclear norm regularized loop optimization for tensor network
Physical Review ResearchWe propose a loop optimization algorithm based on nuclear norm regularization for the tensor network. The key ingredient of this scheme is to introduce a rank penalty term proposed in the context of data processing.
Kenji Homma +2 more
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Numerical stability and tensor nuclear norm
Numerische Mathematik, 2023 25 pages, 7 ...
Zhen Dai, Lek-Heng Lim
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Nonlinear Transform Induced Tensor Nuclear Norm for Tensor Completion
Journal of Scientific Computing, 2022 Nonlinear transform, tensor nuclear norm, proximal alternating minimization, tensor ...
Ben-Zheng Li +4 more
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On Tensor Completion via Nuclear Norm Minimization [PDF]
Foundations of Computational Mathematics, 2015 Many problems can be formulated as recovering a low-rank tensor. Although an increasingly common task, tensor recovery remains a challenging problem because of the delicacy associated with the decomposition of higher order tensors. To overcome these difficulties, existing approaches often proceed by unfolding tensors into matrices and then apply ...
Ming Yuan 0001, Cun-Hui Zhang
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Nuclear norm of higher-order tensors
Mathematics of Computation, 2017 23 ...
Shmuel Friedland, Lek-Heng Lim
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Dynamic Cardiac MRI Reconstruction Using Combined Tensor Nuclear Norm and Casorati Matrix Nuclear Norm Regularizations [PDF]
, 2022 Low-rank tensor models have been applied in accelerating dynamic magnetic resonance imaging (dMRI). Recently, a new tensor nuclear norm based on t-SVD has been proposed and applied to tensor completion.
Hu, Yue, Zhang, Yinghao
core +1 more source
Real Color Image Denoising Using t-Product- Based Weighted Tensor Nuclear Norm Minimization
IEEE Access, 2019 Color images can be seen as third-order tensors with column, row and color modes. Considering two inherent characteristics of a color image including the non-local self-similarity (NSS) and the cross-channel correlation, we extract non-local similar ...
Min Liu, Xinggan Zhang, Lan Tang
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SURE based truncated tensor nuclear norm regularization for low rank tensor completion [PDF]
, 2021 Low rank tensor completion aims to recover the underlying low rank tensor obtained from its partial observations, this has a wide range of applications in Signal Processing and Machine Learning.
Morison, Gordon, Gordon Morison
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