Bayesian Robust Tensor Ring Decomposition for Incomplete Multiway Data-Reference-Cited by-同舟云学术

Bayesian Robust Tensor Ring Decomposition for Incomplete Multiway Data

Published:2024-07 Issue:7 Volume:54 Page:4005-4018
ISSN:2168-2216
Container-title:IEEE Transactions on Systems, Man, and Cybernetics: Systems
language:
Short-container-title:IEEE Trans. Syst. Man Cybern, Syst.

Author:

Huang Zhenhao¹^ORCID,Qiu Yuning²^ORCID,Chen Xinqi³^ORCID,Sun Weijun⁴^ORCID,Zhou Guoxu¹^ORCID

Affiliation:

1. School of Automation and the Key Laboratory of Intelligent Detection and the Internet of Things in Manufacturing, Ministry of Education, Guangdong University of Technology, Guangzhou, China

2. School of Automation, Guangdong University of Technology, Guangzhou, China

3. School of Automation and the Key Laboratory of Intelligent Information Processing and System Integration of IoT, Ministry of Education, Guangdong University of Technology, Guangzhou, China

4. 111 Center for Intelligent Batch Manufacturing Based on IoT Technology and the Guangdong Key Laboratory of IoT Information Technology, Guangdong University of Technology, Guangzhou, China

Funder

National Natural Science Foundation of China

Guangdong Natural Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6221021/10559914/10490147.pdf?arnumber=10490147

Reference67 articles.

1. Canonical polyadic decomposition (CPD) of big tensors with low multilinear rank

2. Efficient Nonnegative Tucker Decompositions: Algorithms and Uniqueness

3. A dynamic hypergraph regularized non-negative tucker decomposition framework for multiway data analysis

4. A Generalized Graph Regularized Non-Negative Tucker Decomposition Framework for Tensor Data Representation

5. Approximately orthogonal nonnegative Tucker decomposition for flexible multiway clustering