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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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書目詳細資料
Main Authors: Belabbas, Mohamed-Ali, Wolfe, Patrick J.
格式: Artigo
語言:Inglês
出版: The Royal Society Publishing 2009
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在線閱讀: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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