PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Bayesian Agglomerative Clustering with Coalescents
Yee Whye Teh, Hal Daume III and Daniel Roy
In: NIPS 2007, 03 Dec - 08 Dec 2007, Vancouver, Canada.

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.

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:3790
Deposited By:Yee Whye Teh
Deposited On:25 February 2008