Low-rank tensor completion using matrix factorization based on tensor train rank and total variation

DOI10.1007/s10915-019-01044-8zbMath1466.94005OpenAlexW2970760100WikidataQ127302141 ScholiaQ127302141MaRDI QIDQ2333730

Teng-Yu Ji, Xi-Le Zhao, Meng Ding, Ting-Zhu Huang, Jing Hua Yang

Publication date: 13 November 2019

Published in: Journal of Scientific Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10915-019-01044-8

zbMATH Keywords

total variationlow-rank tensor completiontensor train rankblock successive upper-bound minimization

Mathematics Subject Classification ID

Numerical optimization and variational techniques (65K10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Direct numerical methods for linear systems and matrix inversion (65F05)

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