Videos

Fitting manifolds to data

Presenter
April 7, 2018
Abstract
The problems come in two flavors.   Extrinsic Flavor: Given a point cloud in R^N sampled from an unknown probability density, how can we decide whether that probability density is concentrated near a low-dimensional manifold M with reasonable geometry? If such an M exists, how can we find it? (Joint work with S. Mitter and H. Narayanan)   Intrinsic Flavor: How can we decide whether a given finite metric space is approximately isometric (in an appropriate sense) to an epsilon-net in a manifold M with reasonable geometry? If such an M exists, how can we find it?   (Joint work with S.Ivanov, Y. Kurylev, M. Lassas and H. Narayanan)