Not enough data to create a plot.
Try a different view from the menu above.
Belkin, Mikhail
Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering
Belkin, Mikhail, Niyogi, Partha
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 manifoldembedded in a higher dimensional space. The algorithm provides a computationally efficient approach to nonlinear dimensionalityreduction that has locality preserving properties and a natural connection to clustering.