Nested Hierarchical Dirichlet Processes

@article{Paisley2015NestedHD,
  title={Nested Hierarchical Dirichlet Processes},
  author={John W. Paisley and Chong Wang and David M. Blei and Michael I. Jordan},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2015},
  volume={37},
  pages={256-270}
}
  • John W. Paisley, Chong Wang, +1 author Michael I. Jordan
  • Published 2015
  • Computer Science, Medicine, Mathematics
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • We develop a nested hierarchical Dirichlet process (nHDP) for hierarchical topic modeling. The nHDP generalizes the nested Chinese restaurant process (nCRP) to allow each word to follow its own path to a topic node according to a per-document distribution over the paths on a shared tree. This alleviates the rigid, single-path formulation assumed by the nCRP, allowing documents to easily express complex thematic borrowings. We derive a stochastic variational inference algorithm for the model… CONTINUE READING

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    A Nested HDP for Hierarchical Topic Models

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    Bayesian Nonparametric Learning for Hierarchical and Sparse Topics

    • Jen-Tzung Chien
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    • IEEE/ACM Transactions on Audio, Speech, and Language Processing
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    Efficient Methods for Inferring Large Sparse Topic Hierarchies

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    References

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    SHOWING 1-10 OF 28 REFERENCES

    Latent Dirichlet Allocation

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    HIGHLY INFLUENTIAL

    Stochastic variational inference

    VIEW 3 EXCERPTS