The Theory and Practice of Highly Scalable Gaussian Process Regression with Nearest Neighbours

Robert Allison, Tomasz Maciazek, Anthony Stephenson

Gaussian process ($GP$) regression is a widely used non-parametric modeling tool, but its cubic complexity in the training size limits its use on massive data sets. A practical rem…