Topic: Estimating Gaussian mixtures using sparse polynomial moment systems

Next in our fall seminar series, we welcome Dr. Julia Lindberg from the University of Texas at Austin.

Abstract:
The method of moments is a statistical technique for density estimation that solves a system of moment equations to estimate the parameters of an unknown distribution. A fundamental question critical to understanding identifiability asks how many moment equations are needed to get finitely many solutions and how many solutions there are. We answer this question for classes of Gaussian mixture models using the tools of polyhedral geometry. Using these results, we present a homotopy method to perform parameter recovery, and therefore density estimation, for high dimensional Gaussian mixture models. The number of paths tracked in our method scales linearly in the dimension.

You can see the presentation live at UTSA San Pedro I in the Yotta Room430.

Those who cannot attend in-person are welcome to tune in virtually through Zoom: https://utsa.zoom.us/j/91049981814.