Robust Low-Rank Tensor Recovery with Rectification and Alignment

Low-rank tensor recovery in the presence of sparse but arbitrary errors is an important problem with many practical applications. In this work, we propose a general framework that recovers low-rank tensors, in which the data can be deformed by some unknown transformations and corrupted by arbitrary...

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Veröffentlicht in:IEEE transactions on pattern analysis and machine intelligence. - 1979. - 43(2021), 1 vom: 22. Jan., Seite 238-255
1. Verfasser: Zhang, Xiaoqin (VerfasserIn)
Weitere Verfasser: Wang, Di, Zhou, Zhengyuan, Ma, Yi
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2021
Zugriff auf das übergeordnete Werk:IEEE transactions on pattern analysis and machine intelligence
Schlagworte:Journal Article