Variational Bayesian Multinomial Probit Regression with Gaussian Process Priors

Abstract

It is well known in the statistics literature that augmenting binary and polychotomous response models with gaussian latent variables enables exact Bayesian analysis viaGibbs sampling from the parameter posterior. By adopting such a data augmentation strategy, dispensing with priors over regression coefficients in favor of gaussian process (GP) priors over… (More)
DOI: 10.1162/neco.2006.18.8.1790

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