Wei Wu
Associate Professor of Statistics
Florida State University
Metric-based Function Registration and Its Applications
ABSTRACT
In this talk, I will present my research on function registration over the past few years. Focusing on statistical analysis on functional data, we have recently developed a novel geometric framework to compare, align, average, and model a collection of random functional observations, where the key step is to find an optimal time warping between two functions for a feature-to-feature alignment. This framework is based on extending the nonparametric version of the Fisher-Rao Riemannian metric to general function spaces, and relies on the fact that this metric is invariant to identical warpings of its arguments. The theoretical underpinning of this new method is established by proving the consistency under a semi-parametric model. We demonstrate this new framework using experimental data in various application domains such as ECG bio-signals, proteomics data, 3D protein structures. Finally, I will present the latest research problems we are working on under this registration framework.
DATE: Wednesday, April 13, 2016
TIME: 4:00 pm – 5:00 pm
PLACE: Philip E. Austin Bldg., Rm. 105
Coffee will be served at 3:30 in the Noether Lounge (AUST 326)
For more information, contact: Tracy Burke at tracy.burke@uconn.edu