Robust Low-Tubal-Rank Tensor Completion Based on Tensor Factorization and Maximum Correntopy Criterion

The goal of tensor completion is to recover a tensor from a subset of its entries, often by exploiting its low-rank property. Among several useful definitions of tensor rank, the low tubal rank was shown to give a valuable characterization of the inherent low-rank structure of a tensor. While some l...

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Bibliographic Details

Published in:	IEEE transaction on neural networks and learning systems Vol. 35; no. 10; pp. 14603 - 14617
Main Authors:	He, Yicong, Atia, George K.
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.10.2024
Subjects:	Alternating minimization Computational modeling correntropy half-quadratic (HQ) Linear programming Matrix decomposition Measurement uncertainty Minimization Signal processing algorithms tensor completion tensor factorization Tensors
ISSN:	2162-237X, 2162-2388, 2162-2388
Online Access:	Get full text
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