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Center for Nonlinear Studies |
In this talk I will discuss our work on manifold learning and its applications to data representation, semi-supervised and unsupervised learning. In particular, I will discuss the significance of the Laplace operator on the manifold and its connections to the heat diffusions. I will show some theoretical results on reconstructing Laplace operators and their eigenfunctions from point-cloud data and various applications, particularly to dimensionality reduction and semi-supervised learning.
Host: Ron Pistone, pistone@lanl.gov, 7-3874