Variational Gaussian Process Classifiers
David J C MacKay and Mark N Gibbs
Gaussian processes are a promising non-linear interpolation
tool \cite{williams:95,williams_rasmussen:96}, but it is not
straightforward to solve classification problems with them. In this paper
the variational methods of \citeasnoun{jaakkola_jordan:bounds} are applied
to Gaussian processes to produce an efficient Bayesian binary classifier.
Submitted to IEEE Transactions on Neural Networks
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