Results 251 to 260 of about 1,664 (280)
Some of the next articles are maybe not open access.
The Twist Tensor Nuclear Norm for Video Completion
IEEE Transactions on Neural Networks and Learning Systems, 2017In 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 ...
Wenrui Hu +2 more
exaly +3 more sources
Unifying tensor factorization and tensor nuclear norm approaches for low-rank tensor completion
Neurocomputing, 2021 Abstract Low-rank tensor completion (LRTC) has gained significant attention due to its powerful capability of recovering missing entries. However, it has to repeatedly calculate the time-consuming singular value decomposition (SVD). To address this drawback, we, based on the tensor-tensor product (t-product), propose a new LRTC method-the unified ...
Du S. +4 more
openaire +2 more sources
A Tensor Regularized Nuclear Norm Method for Image and Video Completion
Journal of Optimization Theory and Applications, 2021 In the present paper, we propose two new methods for tensor completion of third-order tensors. The proposed methods consist in minimizing the average rank of the underlying tensor using its approximate function, namely the tensor nuclear norm.
Abdeslem Hafid Bentbib +3 more
openaire +4 more sources
Sparse and Truncated Nuclear Norm Based Tensor Completion
Neural Processing Letters, 2016One of the main difficulties in tensor completion is the calculation of the tensor rank. Recently a tensor nuclear norm, which is equal to the weighted sum of matrix nuclear norms of all unfoldings of the tensor, was proposed to address this issue. However, in this approach, all the singular values are minimized simultaneously.
Chi-Sing Leung +2 more
exaly +2 more sources
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
Xiongjun Zhang, Michael K Ng
exaly +2 more sources
Internet traffic tensor completion with tensor nuclear norm
Computational Optimization and Applications, 2023zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Can Li, Yannan Chen, Dong-Hui Li
openaire +1 more source
Infrared Small Target Detection Based on Partial Sum of the Tensor Nuclear Norm
Remote Sensing, 2019 Excellent performance, real time and strong robustness are three vital requirements for infrared small target detection. Unfortunately, many current state-of-the-art methods merely achieve one of the expectations when coping with highly complex scenes ...
Zhenming Peng, Peng Zhenming
exaly +2 more sources
Truncated nuclear norm minimization for tensor completion
2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM), 2014In this paper, a tensor n-mode matrix unfolding truncated nuclear norm is proposed, which is extended from the matrix truncated nuclear norm, to tensor completion problem. The alternating direction method of multipliers is utilized to solve this optimization problem.
Longting Huang +3 more
openaire +1 more source
Tensor Nuclear Norm LPV Subspace Identification
IEEE Transactions on Automatic Control, 2018Linear parameter varying (LPV) subspace identification methods suffer from an exponential growth in number of parameters to estimate. This results in problems with ill-conditioning. In literature, attempts have been made to address the ill-conditioning by using regularization. Its effectiveness hinges on suitable a priori knowledge.
Bilal Gunes +2 more
openaire +1 more source
Further results on tensor nuclear norms
Calcolo, 2023zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +2 more sources