Tensor Factorization-Based Method for Tensor Completion with Spatio-temporal Characterization

Quan Yu (), Xinzhen Zhang () and Zheng-Hai Huang ()
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Quan Yu: Hunan University
Xinzhen Zhang: Tianjin University
Zheng-Hai Huang: Tianjin University

Journal of Optimization Theory and Applications, 2023, vol. 199, issue 1, No 13, 337-362

Abstract: Abstract In this paper, we propose a novel tensor factorization-based method for the third-order tensor completion problem with spatio-temporal characterization. For this aim, we consider tensor fibered rank, which extends tubal rank, to improve the flexibility and accuracy of data characterization. Based on this rank, we apply a factorization-based method to complete the third-order low-rank tensors with spatio-temporal characteristics, which are intrinsic features of image, video and internet traffic tensor data. The model not only makes good use of the low-rank structure of tensors, but also takes into account the spatio-temporal characteristics of the data. Finally, we report numerical results on completing image, video and internet traffic data. The results demonstrate that our method outperforms some existing methods.

Keywords: Tensor completion; Tensor factorization; Tensor fibered rank; Spatio-temporal characteristics; 15A69; 46B28 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10957-023-02287-0

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