Results 31 to 40 of about 240,751 (277)
Bounds on Dimension Reduction in the Nuclear Norm [PDF]
, 2019 $ \newcommand{\schs}{\scriptstyle{\mathsf{S}}_1} $For all $n \ge 1$, we give an explicit construction of $m \times m$ matrices $A_1,\ldots,A_n$ with $m = 2^{\lfloor n/2 \rfloor}$ such that for any $d$ and $d \times d$ matrices $A'_1,\ldots,A'_n$ that ...
B Brinkman +10 more
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2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI), 2022 4 pages, 3 figures, 1 table, accepted in IEEE ISBI ...
Zhang, Yinghao, Hu, Yue
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Mathematics, 2020 Reconstruction of 3D objects in various tomographic measurements is an important problem which can be naturally addressed within the mathematical framework of 3D tensors.
Mohamed Ibrahim Assoweh +2 more
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The Ideal of σ-Nuclear Operators and Its Associated Tensor Norm
Mathematics, 2020 We introduce a new tensor norm ( σ -tensor norm) and show that it is associated with the ideal of σ -nuclear operators. In this paper, we investigate the ideal of σ -nuclear operators and the σ -tensor norm.
Ju Myung Kim, Keun Young Lee
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Traffic Data Restoration Method Based on Tensor Weighting and Truncated Nuclear Norm [PDF]
Jisuanji kexue, 2023 The problem of missing data seriously affects a series of activities in intelligent transportation systems,such as monitoring traffic dynamics,predicting traffic flow,and deploying traffic planning through data.Therefore,a traffic flow data ...
WU Jiangnan, ZHANG Hongmei, ZHAO Yongmei, ZENG Hang, HU Gang
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Rank aggregation via nuclear norm minimization
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, 2011 The process of rank aggregation is intimately intertwined with the structure of skew-symmetric matrices. We apply recent advances in the theory and algorithms of matrix completion to skew-symmetric matrices. This combination of ideas produces a new method for ranking a set of items.
Gleich, David F., Lim, Lek-Heng
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Spectral norm and nuclear norm of a third order tensor
Journal of Industrial & Management Optimization, 2022 <p style="text-indent:20px;">The spectral norm and the nuclear norm of a third order tensor play an important role in the tensor completion and recovery problem. We show that the spectral norm of a third order tensor is equal to the square root of the spectral norm of three positive semi-definite biquadratic tensors, and the square roots of the ...
Qi, L, Hu, S, Xu, Y
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Truncated Nuclear Norm Minimization for Image Restoration Based On Iterative Support Detection [PDF]
, 2014 Recovering a large matrix from limited measurements is a challenging task arising in many real applications, such as image inpainting, compressive sensing and medical imaging, and this kind of problems are mostly formulated as low-rank matrix ...
Su, Xinhua, Wang, Yilun
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Weighted Tensor Nuclear Norm Minimization for Color Image Restoration
IEEE Access, 2019 Non-local self-similarity (NLSS) is widely used as prior information in an image restoration method. In particular, a low-rankness-based prior has a significant effect on performance.
Kaito Hosono +2 more
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In-network Sparsity-regularized Rank Minimization: Algorithms and Applications [PDF]
, 2012 Given a limited number of entries from the superposition of a low-rank matrix plus the product of a known fat compression matrix times a sparse matrix, recovery of the low-rank and sparse components is a fundamental task subsuming compressed sensing ...
Giannakis, Georgios B. +2 more
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