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Canonical Correlation Analysis on Riemannian Manifolds and Its Applications
Canonical correlation analysis (CCA) is a widely used statistical technique to capture correlations between two sets of multi-variate random variables and has found a multitude of applications in computer vision, medical imaging and machine learning. The classical formulation assumes that the data l...
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| Main Authors: | , , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
2014
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| Assuntos: | |
| Acceso en liña: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4194269/ https://ncbi.nlm.nih.gov/pubmed/25317426 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/978-3-319-10605-2_17 |
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