Date: 2011-09-23

Time: 15:30-16:30

Location: BURN 1205

Abstract:

In this talk, we give a basic introduction to Sumio Watanabe’s Singular Learning Theory, as outlined in his book “Algebraic Geometry and Statistical Learning Theory”. Watanabe’s key insight to studying singular models was to use a deep result in algebraic geometry known as Hironaka’s Resolution of Singularities. This result allows him to reparametrize the model in a normal form so that central limit theorems can be applied. In the second half of the talk, we discuss new algebraic methods where we define fiber ideals for discrete/Gaussian models. We show that the key to understanding the singular model lies in monomializing its fiber ideal.

Speaker

Shaowei Lin is a Postdoctoral Fellow at UC Berkeley. He received a B.Sc. from Stanford and a Ph.D. from UC Berkeley under the supervision of Bernd Sturmfels.