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Gaussian processes are a promising nonlinear regression tool, but it is not straightforward to solve classification problems with them. In this paper the variational methods of Jaakkola and Jordan are applied to Gaussian processes to produce an efficient Bayesian binary classifier.
Mackay et al. (Sat,) studied this question.
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