Making Predictions using Large Scale Gaussian Processes
One of the key problems that arises in many areas is to estimate a potentially nonlinear function [tex] G(x, \theta)[/tex] given input and output samples [tex] ( X,y ) [/tex] so that [tex]y approx G(x, \theta)[/tex].


There are many approaches to addressing this regression problem. Neural networks, regression …