An Empirical Study of Stochastic Variational Algorithms for the Beta Bernoulli Process

26 Jun 2015Amar ShahDavid A. KnowlesZoubin Ghahramani

Stochastic variational inference (SVI) is emerging as the most promising candidate for scaling inference in Bayesian probabilistic models to large datasets. However, the performance of these methods has been assessed primarily in the context of Bayesian topic models, particularly latent Dirichlet allocation (LDA)... (read more)

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