Robust Tensor Method Based on Correntropy and Tensor Singular Value Decomposition for Cancer Genomics Data-Reference-Cited by-同舟云学术

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Robust Tensor Method Based on Correntropy and Tensor Singular Value Decomposition for Cancer Genomics Data

Published:2021-12-09 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
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Author:

Qiao Qian,Gao Ying-Lian,Yuan Sha-Sha,Liu Jin-Xing

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9669261/9669139/09669785.pdf?arnumber=9669785

Reference28 articles.

1. Robust Matrix Completion via Maximum Correntropy Criterion and Half-Quadratic Optimization

2. Robust Tensor Decomposition for Image Representation Based on Generalized Correntropy

3. Third-Order Tensors as Operators on Matrices: A Theoretical and Computational Framework with Applications in Imaging

4. A Unified Alternating Direction Method of Multipliers by Majorization Minimization

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. t-Product-Based Dynamical Systems;Synthesis Lectures on Mathematics & Statistics;2024

2. Tensor Robust PCA Based on Transformed Tensor Singular Value Decomposition for Cancer Genomic Data;2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM);2022-12-06

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