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Nonlinear Dimensionality Reduction II: Diffusion Maps

Nonlinear Dimensionality Reduction II: Diffusion Maps

陈傲天
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Making a graph from the data; random walks on this graph. The diffusion operator, a.k.a. Laplacian. How the Laplacian encodes the shape of the data. Eigenvectors of the Laplacian as coordinates. Connection to page-rank. Advantages when data are not actually on a manifold.
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