Kernel Adaptive Metropolis-Hastings

19 Jul 2013Dino SejdinovicHeiko StrathmannMaria Lomeli GarciaChristophe AndrieuArthur Gretton

A Kernel Adaptive Metropolis-Hastings algorithm is introduced, for the purpose of sampling from a target distribution with strongly nonlinear support. The algorithm embeds the trajectory of the Markov chain into a reproducing kernel Hilbert space (RKHS), such that the feature space covariance of the samples informs the choice of proposal... (read more)

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