Teh, YW and Daumé, H and Roy, D (2009) Bayesian agglomerative clustering with coalescents. Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference.Full text not available from this repository.
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.
|Divisions:||Div F > Computational and Biological Learning|
|Depositing User:||Cron Job|
|Date Deposited:||15 Dec 2015 13:29|
|Last Modified:||18 Jan 2016 06:19|