CUED Publications database

Pitman Yor Diffusion Trees for Bayesian Hierarchical Clustering.

Knowles, DA and Ghahramani, Z (2015) Pitman Yor Diffusion Trees for Bayesian Hierarchical Clustering. IEEE Trans Pattern Anal Mach Intell, 37. pp. 271-289.

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Abstract

In this paper we introduce the Pitman Yor Diffusion Tree (PYDT), a Bayesian non-parametric prior over tree structures which generalises the Dirichlet Diffusion Tree [30] and removes the restriction to binary branching structure. The generative process is described and shown to result in an exchangeable distribution over data points. We prove some theoretical properties of the model including showing its construction as the continuum limit of a nested Chinese restaurant process model. We then present two alternative MCMC samplers which allow us to model uncertainty over tree structures, and a computationally efficient greedy Bayesian EM search algorithm. Both algorithms use message passing on the tree structure. The utility of the model and algorithms is demonstrated on synthetic and real world data, both continuous and binary.

Item Type: Article
Subjects: UNSPECIFIED
Divisions: Div F > Computational and Biological Learning
Depositing User: Cron Job
Date Deposited: 17 Jul 2017 19:45
Last Modified: 23 Nov 2017 03:36
DOI: