Applied Math And Analysis Seminar
Monday, January 23, 2012, 4:30pm, 119 Physics
Matthew Hirn (Yale University)
Diffusion maps for changing data

Abstract:

Recently there has been a large class of research that utilizes nonlinear mappings into low dimensional spaces in order to organize potentially high dimensional data. Examples include, but are not limited to, locally linear embedding (LLE), ISOMAP, Hessian LLE, Laplacian eigenmaps, and diffusion maps. In this talk we will focus on the latter, and in particular consider how to generalize diffusion maps to the setting in which we are given a data set that evolves over time or changes depending on some set of parameters. Along with describing the current theory, various synthetic and real world examples will be presented to illustrate these ideas in practice. [video]

---

Generated at 3:07am Thursday, April 25, 2024 by Mcal.   Top * Reload * Login