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Collapsed variational inference for HDP

Abstract:

A wide variety of Dirichlet-multinomial 'topic' models have found interesting applications in recent years. While Gibbs sampling remains an important method of inference in such models, variational techniques have certain advantages such as easy assessment of convergence, easy optimization without the need to maintain detailed balance, a bound on the marginal likelihood, and side-stepping of issues with topic-identifiability. The most accurate variational technique thus far, namely collapsed ...

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Journal:
Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference More from this journal
Publication date:
2009-01-01
Language:
English
Pubs id:
pubs:353233
UUID:
uuid:ac3f313c-1899-43a3-9d70-777c1f0cd680
Local pid:
pubs:353233
Source identifiers:
353233
Deposit date:
2013-11-16

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