Low-Rank Tensor Completion Using Matrix Factorization Based on Tensor Train Rank and Total Variation-Reference-Cited by-同舟云学术

Low-Rank Tensor Completion Using Matrix Factorization Based on Tensor Train Rank and Total Variation

Published:2019-08-30 Issue:2 Volume:81 Page:941-964
ISSN:0885-7474
Container-title:Journal of Scientific Computing
language:en
Short-container-title:J Sci Comput

Author:

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

Funder

the National Science Foundation of China

the Fundamental Research Funds for the Central Universities

Science Strength Promotion Programme of UESTC

Publisher

Springer Science and Business Media LLC

Subject

Computational Theory and Mathematics,General Engineering,Theoretical Computer Science,Software,Applied Mathematics,Computational Mathematics,Numerical Analysis

Link

http://link.springer.com/content/pdf/10.1007/s10915-019-01044-8.pdf

Reference37 articles.

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