Most previous inference algorithms for DP-based models involve sampling (Escobar and West, 1995;Teh et al., 2006).
we chose to use variational inference (Blei and Jordan, 2005), which provides a fast deterministic alternative to sampling, hence avoiding issues of diagnosing convergence and aggregating samples.