Journal article

Stick-breaking Construction for the Indian Buffet Process

Teh Y, Dilan G, Ghahramani Z ...see all

Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, vol. 2 (2007) pp. 556-563

  • 153

    Readers

    Mendeley users who have this article in their library.
  • 24

    Citations

    Citations of this article.
Sign in to save reference

Abstract

The Indian buffet process (IBP) is a Bayesian nonparametric distribution whereby objects are modelled using an unbounded number of latent features. In this paper we derive a stick-breaking representation for the IBP. Based on this new rep- resentation, we develop slice samplers for the IBP that are efficient, easy to implement and are more generally applicable than the currently available Gibbs sampler. This representation, along with the work of Thibaux and Jordan (17), also illuminates interesting theoretical connec- tions between the IBP, Chinese restaurant pro- cesses, Beta processes and Dirichlet processes.

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document

  • ISSN: 15324435
  • PUI: 365009410
  • SGR: 84857251974
  • SCOPUS: 2-s2.0-84857251974

Authors

  • Yee Whye Teh

  • Görür Dilan

  • Zoubin Ghahramani

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free