Hybrid variational/Gibbs collapsed inference in topic models
Variational Bayesian inference and (collapsed) Gibbs sampling are the two important classes of inference algorithms for Bayesian networks. Both have their advantages and disadvantages: collapsed Gibbs sampling is unbiased but is also inefficient for large count values and requires averaging over man...
| Main Authors: | , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
2008
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