2012 PracticalCollapsedVariationalBa

• (Sato et al., 2012) ⇒ Issei Sato, Kenichi Kurihara, and Hiroshi Nakagawa. (2012). “Practical Collapsed Variational Bayes Inference for Hierarchical Dirichlet Process.” In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2012). ISBN:978-1-4503-1462-6 doi:10.1145/2339530.2339550

Subject Headings:

Cited By

• http://scholar.google.com/scholar?q=%222012%22+Practical+Collapsed+Variational+Bayes+Inference+for+Hierarchical+Dirichlet+Process
• http://dl.acm.org/citation.cfm?id=2339530.2339550&preflayout=flat#citedby

Quotes

Author Keywords

• Collapsed variational bayes inference; [[hierarchical dirichlet process; latent dirichlet allocation; nonparametric bayes; nonparametric statistics

Abstract

We propose a novel collapsed variational Bayes (CVB) inference for the hierarchical Dirichlet process (HDP). While the existing CVB inference for the HDP variant of latent Dirichlet allocation (LDA) is more complicated and harder to implement than that for LDA, the proposed algorithm is simple to implement, does not require variance counts to be maintained, does not need to set hyper-parameters, and has good predictive performance.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2012 PracticalCollapsedVariationalBa	Hiroshi Nakagawa Issei Sato Kenichi Kurihara			Practical Collapsed Variational Bayes Inference for Hierarchical Dirichlet Process				10.1145/2339530.2339550		2012