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Dependent Hierarchical Normalized Random Measures for Dynamic Topic Modeling Changyou Chen, Nan Ding and Wray Buntine IC

Dependent Hierarchical Normalized Random Measures for Dynamic Topic Modeling Changyou Chen, Nan Ding and Wray Buntine ICML 2012. Presented by: Mingyuan Zhou Duke University, ECE October 24, 2012. Introduction. NRM: normalized random measures with independent increments

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Dependent Hierarchical Normalized Random Measures for Dynamic Topic Modeling Changyou Chen, Nan Ding and Wray Buntine IC

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  1. Dependent Hierarchical Normalized Random Measures for Dynamic Topic ModelingChangyou Chen, Nan Ding and Wray BuntineICML 2012 Presented by: Mingyuan Zhou Duke University, ECE October 24, 2012

  2. Introduction • NRM: normalized random measures with independent increments • Superposition, subsampling and point transition of NRM • Dependent hierarchical NRM • Dynamic topic modeling

  3. Normalized Random Measures • Poisson process • Completely random measures (CRM)

  4. Normalized Random Measures • Completely random measures (CRM)

  5. Normalized Random Measures • Slice sampling NRMs Ref: Griffin, J.E. and Walker, S.G. Posterior simulation of normalized random measure mixtures. J. Comput. Graph. Stat., 2011.

  6. Normalized Random Measures • Normalized generalized gamma process

  7. Dynamic topic modeling with dependent hierarchical NRMs • Ideas: • Inherit topics from the previous time frame through three dependency operators: • Superposition • Subsampling • Point transition • Generate new topics

  8. Dynamic topic modeling with dependent hierarchical NRMs

  9. Dynamic topic modeling with dependent hierarchical NRMs

  10. Dynamic topic modeling with dependent hierarchical NRMs

  11. Dynamic topic modeling with dependent hierarchical NRMs • Properties of the dependence operators

  12. Dynamic topic modeling with dependent hierarchical NRMs • Reformulated model

  13. Dynamic topic modeling with dependent hierarchical NRMs • Original and reformulated model

  14. Sampling • Sampling under the Chinese restaurant metaphor

  15. Sampling • Sampling under the Chinese restaurant metaphor

  16. Sampling

  17. Sampling

  18. Sampling

  19. Experiments • Power-law in the NGG

  20. Experiments

  21. Experiments

  22. Experiments

  23. Experiments

  24. Experiments

  25. Conclusions

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