Title: Exact Hamiltonian Monte Carlo for Binary Distributions
Abstract: I will present a new approach to sample from generic binary distributions, based on an exact Hamiltonian Monte Carlo algorithm applied to a piecewise continuous augmentation of the binary distribution of interest. An extension of this idea to distributions over mixtures of binary and continuous variables permits sampling from posteriors of linear and probit regression models with spike-and-slab priors and truncated parameters.
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