Results 241 to 250 of about 1,952,092 (277)

Reshaped Tensor Nuclear Norms for Higher Order Tensor Completion [PDF]

Machine Learning, 2021
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hiroshi Mamitsuka, Kishan Wiamalwarne
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Symmetric Tensor Nuclear Norms [PDF]

SIAM Journal on Applied Algebra and Geometry, 2017
25 ...
Jiawang Nie
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Bounds on the Spectral Norm and the Nuclear Norm of a Tensor Based on Tensor Partitions [PDF]

SIAM Journal on Matrix Analysis and Applications, 2016
Summary: It is known that computing the spectral norm and the nuclear norm of a tensor is NP-hard in general. In this paper, we provide neat bounds for the spectral norm and the nuclear norm of a tensor based on tensor partitions. The spectral norm (respectively, the nuclear norm) can be lower and upper bounded by manipulating the spectral norms ...
Zhening Li
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Tensor Robust Principal Component Analysis With a New Tensor Nuclear Norm [PDF]

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020
In this paper, we consider the Tensor Robust Principal Component Analysis (TRPCA) problem, which aims to exactly recover the low-rank and sparse components from their sum. Our model is based on the recently proposed tensor-tensor product (or t-product).
Jiashi Feng, Wei Liu, Yudong Chen
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Spectral Norm and Nuclear Norm of a Third Order Tensor

Journal of Industrial and 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 ...
Liqun Qi, Shenglong Hu
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Framelet Representation of Tensor Nuclear Norm for Third-Order Tensor Completion [PDF]

IEEE Transactions on Image Processing, 2020
The main aim of this paper is to develop a framelet representation of the tensor nuclear norm for third-order tensor completion. In the literature, the tensor nuclear norm can be computed by using tensor singular value decomposition based on the discrete Fourier transform matrix, and tensor completion can be performed by the minimization of the tensor ...
Michael Ng, Ting-Zhu Huang, Xi-Le Zhao
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Internet traffic tensor completion with tensor nuclear norm

Computational Optimization and Applications, 2023
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Can Li, Yannan Chen, Dong-Hui Li
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Weighted Tensor Nuclear Norm Minimization for Tensor Completion Using Tensor-SVD

Pattern Recognition Letters, 2020
Abstract In this paper, we consider the tensor completion problem, which aims to estimate missing values from limited information. Our model is based on the recently proposed tensor-SVD, which uses the relationships among the color channels in an image or video recovery problem. To improve the availability of the model, we propose the weighted tensor
Xuyun Zhang, Liangfu Lu
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The Twist Tensor Nuclear Norm for Video Completion

IEEE Transactions on Neural Networks and Learning Systems, 2017
In this paper, we propose a new low-rank tensor model based on the circulant algebra, namely, twist tensor nuclear norm (t-TNN). The twist tensor denotes a three-way tensor representation to laterally store 2-D data slices in order. On one hand, t-TNN convexly relaxes the tensor multirank of the twist tensor in the Fourier domain, which allows an ...
Yuan Xie, Dacheng Tao, Wenrui Hu
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A Corrected Tensor Nuclear Norm Minimization Method for Noisy Low-Rank Tensor Completion

SIAM Journal on Imaging Sciences, 2019
© 2019 Society for Industrial and Applied Mathematics. In this paper, we study the problem of low-rank tensor recovery from limited sampling with noisy observations for third-order tensors. A tensor nuclear norm method based on a convex relaxation of the
Michael Ng, Xiongjun Zhang
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