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On landmark selection and sampling in high-dimensional data analysis
In recent years, the spectral analysis of appropriately defined kernel matrices has emerged as a principled way to extract the low-dimensional structure often prevalent in high-dimensional data. Here, we provide an introduction to spectral methods for linear and nonlinear dimension reduction, emphas...
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| Main Authors: | , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
The Royal Society Publishing
2009
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| Assuntos: | |
| Acceso en liña: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2865880/ https://ncbi.nlm.nih.gov/pubmed/19805446 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1098/rsta.2009.0161 |
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