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Online Structure Learning for Feed-Forward and Recurrent Sum-Product Networks
Sum-product networks have recently emerged as an attractive representation due to their dual view as a special type of deep neural network with clear semantics and a special type of probabilistic graphical model for which inference is always tractable.
Online Bayesian Moment Matching for Topic Modeling with Unknown Number of Topics
When the number of topics (or latent groups) is unknown, the Hierarchical Dirichlet Process (HDP) provides an elegant non-parametric extension; however, it is a complex model and it is difficult to incorporate prior knowledge since the distribution over topics is implicit.
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