APPLIED MATH SEMINAR
Speaker: Mauro Maggioni, Department of Mathematics and Computer Science, Duke University
Title: Multiscale geometric methods for noisy point clouds in high dimensions
When/where: Tuesday, November 30th, 4:00 PM, AKW 200
Abstract: We discuss techniques for the geometric multiscale analysis of intrinsically low-dimensional point clouds. We first show how such techniques may be used to estimate the intrinsic dimension of data sets, then discuss a novel geometric multiscale transform, based on what we call geometric wavelets, that leads to novel approximation schemes for point clouds, and dictionary learning methods for data sets. Finally, we apply similar techniques to model estimation when points are sampled from a measure supported on a union of an unknown number of unknown planes of unknown dimensions.