Approximation Methods for Gaussian Process Regression
Joaquin Quinonero Candela, Carl Edward Rasmussen and Christopher Williams
In: Large Scale Kernel Machines Adaptive Computation and Machine Learning . (2006) The MIT Press , Cambridge, MA .

Abstract

A wealth of computationally efficient approximation methods for Gaussian process regression have been recently proposed. We give a unifying overview of sparse approximations, fol lowing Quiñonero-Candela and Rasmussen (2005), and a brief review of approximate matrix-vector multiplication methods.

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