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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Vydané v:	IEEE transaction on neural networks and learning systems Ročník 35; číslo 10; s. 14603 - 14617
Hlavní autori:	He, Yicong, Atia, George K.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.10.2024
Predmet:	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
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