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Bayesian agglomerative clustering with coalescents

Abstract:
We introduce a new Bayesian model for hierarchical clustering based on a prior over trees called Kingman's coalescent. We develop novel greedy and sequential Monte Carlo inferences which operate in a bottom-up agglomerative fashion. We show experimentally the superiority of our algorithms over the state-of-the-art, and demonstrate our approach in document clustering and phylolinguistics.

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Journal:
Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference
Publication date:
2009-01-01
URN:
uuid:3c601d96-e767-4375-8f9f-34c753c99c3d
Source identifiers:
353235
Local pid:
pubs:353235
Language:
English

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