Approximation Methods for Gaussian Process Regression
- Joaquin Quiñonero Candela ,
- Carl Edward Ramussen ,
- Christopher K. I. Williams
A wealth of computationally efficient approximation methods for Gaussian process regression have been recently proposed. We give a unifying overview of sparse approximations, following Quiñonero-Candela and Rasmussen (2005), and a brief review of approximate matrix-vector multiplication methods.