Corpus ID: 7811257

Variational Learning of Inducing Variables in Sparse Gaussian Processes

@inproceedings{Titsias2009VariationalLO,
  title={Variational Learning of Inducing Variables in Sparse Gaussian Processes},
  author={M. Titsias},
  booktitle={AISTATS},
  year={2009}
}
  • M. Titsias
  • Published in AISTATS 2009
  • Mathematics, Computer Science
Sparse Gaussian process methods that use inducing variables require the selection of the inducing inputs and the kernel hyperparameters. We introduce a variational formulation for sparse approximations that jointly infers the inducing inputs and the kernel hyperparameters by maximizing a lower bound of the true log marginal likelihood. The key property of this formulation is that the inducing inputs are defined to be variational parameters which are selected by minimizing the Kullback-Leibler… Expand
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