Domain Adaption Based on Symmetric Matrices Space Bi-Subspace Learning and Source Linear Discriminant Analysis Regularization
At present, Symmetric Positive Definite (SPD) matrix data is the most common non-Euclidean data in machine learning. Because SPD data don’t form a linear space, most machine learning algorithms can not be carried out directly on SPD data. The first purpose of this paper is to propose a ne...
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| Autores principales: | , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
IEEE
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/4dfa2953c2e244aa9f43b97d25fac455 |
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