Parallel Sampling of HDPs using Sub-Cluster Splits

@inproceedings{Chang2014ParallelSO,
  title={Parallel Sampling of HDPs using Sub-Cluster Splits},
  author={Jason Chang and John W. Fisher},
  booktitle={NIPS},
  year={2014}
}
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. 
7 Citations
23 References
Similar Papers

Similar Papers

Loading similar papers…