Algebraic and combinatorial problems arising from maximum likelihood estimation using small datasets

Algebra Seminar
Monday, November 21, 2022 - 1:30pm for 1 hour (actually 50 minutes)
Clough 125 Classroom
Daniel Irving Bernstein – Tulane University Department of Mathematics – dbernstein1@tulane.edu
Papri Dey

Loosely speaking, the maximum likelihood threshold of a statistical model is the fewest number of data points needed to fit the model using maximum likelihood estimation. In this talk, I will discuss combinatorial and algebraic-geometric approaches to studying this poorly understood quantity for a certain class of Gaussian models. This is based on joint work with Sean Dewar, Steven Gortler, Tony Nixon, Meera Sitharam, and Louis Theran