Gamma Processes, Stick-Breaking, and Variational Inference

4 Oct 2014 Anirban Roychowdhury Brian Kulis

While most Bayesian nonparametric models in machine learning have focused on the Dirichlet process, the beta process, or their variants, the gamma process has recently emerged as a useful nonparametric prior in its own right. Current inference schemes for models involving the gamma process are restricted to MCMC-based methods, which limits their scalability... (read more)

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