Title: The maximum likelihood degree and data discriminants of likelihood equations
The maximum likelihood degree (ML degree) is a topological invariant of a variety and in the nicest cases the ML-degree is a signed Euler characteristic. The ML degree measures the algebraic complexity of the maximum likelihood estimation problem in algebraic statistics, which is my motivation for computing these numbers. The first part of the talk will provide an introduction to the ML degree and its connections to topological Euler characteristics. The second part of the talk will offer computational results followed by conjectures.