Parallel Sampling of DP Mixture Models using Sub-Cluster Splits

  title={Parallel Sampling of DP Mixture Models using Sub-Cluster Splits},
  author={Jason Chang and John W. Fisher},
•How can we do non-approximate parallel inference in the Dirichlet process? •Recent work by Lovell, Adams, and Mansingka [2012] and Williamson, Dubey, and Xing [2013] suggested a re-parametrisation of the process to derive such inference. •We show that the approach suggested is impractical due to an extremely unbalanced distribution of the data. •We show that the suggested approach fails most requirements of parallel inference – the load balance is independent of the size of the dataset and the… CONTINUE READING
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