Results 11 to 20 of about 1,664 (280)
Reshaped tensor nuclear norms for higher order tensor completion [PDF]
Machine Learning, 2021 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kishan Wimalawarne, Hiroshi Mamitsuka
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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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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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Multiview Subspace Clustering by an Enhanced Tensor Nuclear Norm [PDF]
IEEE Transactions on Cybernetics, 2022 Despite the promising preliminary results, tensor-singular value decomposition (t-SVD)-based multiview subspace is incapable of dealing with real problems, such as noise and illumination changes. The major reason is that tensor-nuclear norm minimization (TNNM) used in t-SVD regularizes each singular value equally, which does not make sense in matrix ...
Wei Xia 0007 +5 more
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A concise proof to the spectral and nuclear norm bounds through tensor partitions
Open Mathematics, 2019 On estimations of the lower and upper bounds for the spectral and nuclear norm of a tensor, Li established neat bounds for the two norms based on regular tensor partitions, and proposed a conjecture for the same bounds to be hold based on general tensor ...
Kong Xu
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Low-Rank Tensor Completion for Image and Video Recovery via Capped Nuclear Norm [PDF]
IEEE Access, 2019 Inspired by the robustness and efficiency of the capped nuclear norm, in this paper, we apply it to 3D tensor applications and propose a novel low-rank tensor completion method via tensor singular value decomposition (t-SVD) for image and video recovery.
Xi Chen +5 more
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A QoS Prediction Approach Based on Truncated Nuclear Norm Low-Rank Tensor Completion
Sensors, 2022 With the rise of mobile edge computing (MEC), mobile services with the same or similar functions are gradually increasing. Usually, Quality of Service (QoS) has become an indicator to measure high-quality services.
Hong Xia +5 more
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Hyperspectral Image Denoising via Framelet Transformation Based Three-Modal Tensor Nuclear Norm
Remote Sensing, 2021 During the acquisition process, hyperspectral images (HSIs) are inevitably contaminated by mixed noise, which seriously affects the image quality. To improve the image quality, HSI denoising is a critical preprocessing step.
Wenfeng Kong, Yangyang Song, Jing Liu
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Accelerated Tensor Robust Principal Component Analysis via Factorized Tensor Norm Minimization
Applied SciencesIn this paper, we aim to develop an efficient algorithm for the solving Tensor Robust Principal Component Analysis (TRPCA) problem, which focuses on obtaining a low-rank approximation of a tensor by separating sparse and impulse noise.
Geunseop Lee
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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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