Efficient Optimization for Sparse Gaussian Process Regression

We propose an efficient optimization algorithm to select a subset of training data as the inducing set for sparse Gaussian process regression. Previous methods either use different objective functions for inducing set and hyperparameter selection, or else optimize the inducing set by gradient-based...

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Publié dans:IEEE transactions on pattern analysis and machine intelligence. - 1979. - 37(2015), 12 vom: 21. Dez., Seite 2415-27
Auteur principal: Cao, Yanshuai (Auteur)
Autres auteurs: A Brubaker, Marcus, J Fleet, David, Hertzmann, Aaron
Format: Article en ligne
Langue:English
Publié: 2015
Accès à la collection:IEEE transactions on pattern analysis and machine intelligence
Sujets:Journal Article Research Support, Non-U.S. Gov't