Dimensionality Reduction of Tensors Based on Local Homeomorphism and Global Subspace Projection Distance Minimum
Tensors are powerful tools for representing and processing multidimensional data. In this paper, an algorithm of dimension reduction for multidimensional data is proposed. We consider both the global and local structures of the data to fully extract important features. Multiplying a tensor by a matr...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9102301/ |