CMSA Combinatorics, Physics and Probability: Invariant theory for maximum likelihood estimation

Name: CMSA Combinatorics, Physics and Probability: Invariant theory for maximum likelihood estimation
Start: 2022-02-08T09:00:00-05:00
End: 2022-02-08T10:00:00-05:00
Location: Virtually

When: February 8, 2022

9:00 am - 10:00 am

Where: Virtually

Speaker: 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.

https://harvard.zoom.us/j/91799784675?pwd=MS9LV25DWk9RcmJoRVM0K3RGWkFRdz09

Password: 1251442