Kernel methods for spatiotemporal learning with public policy applications

Neyman Seminar
Jan 18, 2017 4:00pm to 5:00pm
Location: 
1011 Evans Hall
Status: 
Happening As Scheduled
In this talk I will highlight the statistical machine learning methods that I am developing, in response to the needs of my social science collaborators, to address public policy questions. My research focuses on flexible nonparametric modeling approaches for spatiotemporal data and scalable inference methods to be able to fit these models to large datasets. Most critically, my models and...
Seth Flaxman, Department of Statistics, Oxford