Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering

@inproceedings{Belkin2001LaplacianEA,
  title={Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering},
  author={Mikhail Belkin and Partha Niyogi},
  booktitle={NIPS},
  year={2001}
}
Drawing on the correspondence between the graph Laplacian, the Laplace-Beltrami operator on a manifold, and the connections to the heat equation, we propose a geometrically motivated algorithm for constructing a representation for data sampled from a low dimensional manifold embedded in a higher dimensional space. The algorithm provides a computationally efficient approach to nonlinear dimensionality reduction that has locality preserving properties and a natural connection to clustering… CONTINUE READING

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