Monte Carlo Structured SVI for Two-Level Non-Conjugate Models

12 Dec 2016 Rishit Sheth Roni Khardon

The stochastic variational inference (SVI) paradigm, which combines variational inference, natural gradients, and stochastic updates, was recently proposed for large-scale data analysis in conjugate Bayesian models and demonstrated to be effective in several problems. This paper studies a family of Bayesian latent variable models with two levels of hidden variables but without any conjugacy requirements, making several contributions in this context... (read more)

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