Low-Rank Tensor Completion by Sum of Tensor Nuclear Norm Minimization
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2940664
Abstract: In this paper, we study the problem of low-rank tensor completion with the purpose of recovering a low-rank tensor from a tensor with partial observed items. To date, there are several different definitions of tensor… read more here.
Keywords: tensor; tensor nuclear; norm minimization; rank tensor ... See more keywords
A Tensor Method Based on Enhanced Tensor Nuclear Norm and Hypergraph Laplacian Regularization for Pan-Cancer Omics Data Analysis
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal of Biomedical and Health Informatics"
DOI: 10.1109/jbhi.2022.3231908
Abstract: As a powerful data representation technique, tensor robust principal component analysis (TRPCA) has been widely used for clustering and feature selection tasks. However, it ignores the significant difference in singular values of tensor data and… read more here.
Keywords: tensor; enhanced tensor; nuclear norm; tensor nuclear ... See more keywords
Randomized Tensor Robust PCA for Noisy Hyperspectral Image Classification
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2023.3251861
Abstract: Removing noise from hyperspectral images can be very beneficial for improving classification accuracy. Recently, tensor robust principal component analysis (TRPCA) has been successfully employed to reduce noise in hyperspectral images. In TRPCA, a minimization involving… read more here.
Keywords: tensor; classification; tensor nuclear; tensor robust ... See more keywords
Tensor Nuclear Norm LPV Subspace Identification
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Automatic Control"
DOI: 10.1109/tac.2018.2800772
Abstract: Linear 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… read more here.
Keywords: lpv subspace; nuclear norm; tensor nuclear; subspace identification ... See more keywords
A Fast Tensor Completion Method Based on Tensor QR Decomposition and Tensor Nuclear Norm Minimization
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Computational Imaging"
DOI: 10.1109/tci.2021.3130977
Abstract: Currently, the tensor completion problem has been paid high attention in the machine learning, especially in the field of computer vision and image processing. The low-rank tensor completion methods based on the tensor singular value… read more here.
Keywords: completion; tensor completion; based tensor; nuclear norm ... See more keywords