Approximation Methods for Gaussian Process Regression

Joaquin Quiñonero Candela, Carl Edward Ramussen, Christopher K. I. Williams

MSR-TR-2007-124 |

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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.