Advanced Lectures on Machine Learning pp 63-71

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3176)

Gaussian Processes in Machine Learning

  • Carl Edward Rasmussen

Abstract

We give a basic introduction to Gaussian Process regression models. We focus on understanding the role of the stochastic process and how it is used to define a distribution over functions. We present the simple equations for incorporating training data and examine how to learn the hyperparameters using the marginal likelihood. We explain the practical advantages of Gaussian Process and end with conclusions and a look at the current trends in GP work.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Carl Edward Rasmussen
    • 1
  1. 1.Max Planck Institute for Biological CyberneticsTübingenGermany

Personalised recommendations