Low-Rank Tensor Thresholding Ridge Regression

Low-Rank Tensor Thresholding Ridge Regression

In the area of subspace clustering, methods combining self-representation and spectral clustering are predominant in recent years. For dealing with tensor data, most existing methods vectorize them into vectors and lose most of the spatial information. For removing noise of the data, most existing m...

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Bibliographic Details
Main Authors: Kailing Guo, Tong Zhang, Xiangmin Xu, Xiaofen Xing
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Tensor
low-rank
subspace clustering
Online Access:https://ieeexplore.ieee.org/document/8852636/

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