CMSA Combinatorics, Physics and Probability: Invariant theory for maximum likelihood estimation
SEMINARS, CMSA EVENTS
Anna Seigal - Harvard University, Math Department
I will talk about work to uncover connections between invariant theory and maximum likelihood estimation. I will describe how norm minimization over a torus orbit is equivalent to maximum likelihood estimation in log-linear models. We will see the role played by polytopes and discuss connections to scaling algorithms. Based on joint work with Carlos Améndola, Kathlén Kohn, and Philipp Reichenbach.