CTF-PSF: Coupled Tensor Factorization with Partially Shared Factors
- Publication Type:
- Conference Proceeding
- Citation:
- Proceedings of the International Joint Conference on Neural Networks, 2018, 2018-July
- Issue Date:
- 2018-10-10
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08489754.pdf | Published version | 1.47 MB |
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© 2018 IEEE. Coupled matrix-tensor factorization has been suc- cessfully applied in various fields in the processing of coupled data. However, the unshared components between coupled data tend to make the joint decomposition inaccurate. In order to solve this problem, in this work, we propose a method to improve the traditional method by combining individual decomposition and coupled decomposition to analyze the shared and unshared components. Numerical experiments are given to illustrate the advantages of the proposed method compared to the existing approaches.
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