Student Seminar Series
DATE: Tuesday, February 13th, 2018, 2:00pm
LOCATION: MSB 1147 (Colloquium Room).
SPEAKERS: Robert Bassett, Graduate Student, Mathematics, UC Davis
TITLE: Trendi-Splines: Density Estimation with Total Variation Penalized Maximum Likelihood Estimation
ABSTRACT: We introduce a new method for nonparametric density estimation on geometric networks. By penalizing a maximum likelihood approach with a total variation penalty, we avoid overfitting and the dirac curse. We provide results which reduce the search space for the estimator from infinite dimensional function space to the finite-dimensional setting, and further demonstrate its computational tractability. We then focus on the asymptotic convergence rate of this density estimation method. Lastly, we review applications to the defense of infrastructure networks.
This seminar series is organized by PhD Students Andrew Blandino, Dmitriy Izyumin, and Benjamin Roycraft.