Thursday, April 26, 2018 - 10:30am - 11:00am
Garvesh Raskutti (University of Wisconsin, Madison)
Consider a multi-variate time series, which may correspond to spike train responses for multiple neurons in a brain, crime event data across multiple regions, and many others. An important challenge associated with these time series models is to estimate an influence network between the d variables, especially when the number of variables d is large meaning we are in the high-dimensional setting. Prior work has focused on parametric vector auto-regressive models. However, parametric approaches are somewhat restrictive in practice.
Subscribe to RSS - SpAM