The time-marginalized coalescent prior for hierarchical clustering

Open Access
Authors
Publication date 2013
Host editors
  • P. Bartlett
  • F.C.N. Pereira
  • C.J.C. Burges
  • L. Bottou
  • K.Q. Weinberger
Book title 26th Annual Conference on Neural Information Processing Systems 2012
Book subtitle December 3-6, 2012, Lake Tahoe, Nevada, USA
ISBN
  • 9781627480031
Series Advances in Neural Information Processing Systems
Volume | Issue number 4
Pages (from-to) 2969-2977
Publisher Red Hook, NY: Curran Associates
Organisations
  • Faculty of Science (FNWI) - Informatics Institute (IVI)
Abstract We introduce a new prior for use in Nonparametric Bayesian Hierarchical Clustering. The prior is constructed by marginalizing out the time information ofKingman’s coalescent, providing a prior over tree structures which we call the Time-Marginalized Coalescent (TMC). This allows for models which factorize the tree structure and times, providing two benefits: more flexible priors may be
constructed and more efficient Gibbs type inference can be used. We demonstrate this on an example model for density estimation and show the TMC achieves competitive experimental results.
Document type Conference contribution
Language English
Published at https://papers.nips.cc/paper/4786-the-time-marginalized-coalescent-prior-for-hierarchical-clustering
Downloads
Supplementary material (Submitted manuscript)
time.pdf (Final published version)
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