Hierarchical Dirichlet Process

A Hierarchical Dirichlet Process is a Dirichlet process with a hierarchical structure.

• See: Clustering, Mixture Model, Nonparametric Bayesian Algorithm, Hierarchical Model, Markov Chain Monte Carlo, Hierarchical LDA.

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References

2011

• http://en.wikipedia.org/wiki/Dirichlet_process#Related_distributions
  • The Pitman–Yor distribution (also known as the 'two-parameter Poisson-Dirichlet process') is a generalisation of the Dirichlet process.
  • The hierarchical Dirichlet process extends the ordinary Dirichlet process for modelling grouped data.

2006

• (Teh et al., 2006) ⇒ Yee Whye Teh, Michael I. Jordan, Matthew J. Beal, and David M. Blei. (2006). “Hierarchical Dirichlet Processes.” In: Journal of the American Statistical Association, 101(476). doi:10.1198/016214506000000302
  • QUOTE: In the current paper we explore a hierarchical approach to the problem of model-based clustering of grouped data. We assume that the data are [[subdivided into a set of groups, and that within each group we wish to find clusters that capture latent structure in the data assigned to that group. The number of clusters within each group is unknown and is to be inferred. Moreover, in a sense that we make precise, we wish to allow clusters to be shared among the groups.

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