Conference Agenda
Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
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Daily Overview |
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High-dimensional statistics and learning Location: 0.004 Session Chair: Martin Wahl | |
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Laplacian eigenmaps for bounded manifolds and the Neumann Laplacian Universität Bielefeld, Germany The spectrum of the Laplace-Beltrami operator encodes essential geometric information about a smooth manifold. In practice, the manifold is unknown, but supports a finite sample of random points. It is then standard to approximate its spectrum by the spectrum of the resulting graph Laplacian. When the manifold is bounded, it is known that the graph Laplacian eigen-converges to the Neumann Laplacian. However, finite sample results, such as convergence rates, are still lacking, and are at the center of this talk. | |
