Parallel Sampling of HDPs using Sub-Cluster Splits

  title={Parallel Sampling of HDPs using Sub-Cluster Splits},
  author={Jason Chang and John W. Fisher},
We develop a sampling technique for Hierarchical Dirichlet process models. The parallel algorithm builds upon [1] by proposing large split and merge moves based on learned sub-clusters. The additional global split and merge moves drastically improve convergence in the experimental results. Furthermore, we discover that cross-validation techniques do not adequately determine convergence, and that previous sampling methods converge slower than were previously expected. 
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