University of Cambridge > Talks.cam > Machine Learning Journal Club > Kingman's coalescent, non-parametric Bayesian agglomerative clustering

Kingman's coalescent, non-parametric Bayesian agglomerative clustering

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact Philip Sterne.

Kingman’s coalescent can be obtained as the continuous/infinite limit of the following process: at each time t there is a population of N individuals; each individual picks a parent at random from the previous generation of individuals, located in time t+1/N.

The paper for journal club will be the NIPS submission by YWT : “Bayesian agglomerative clustering”.

Other relevant papers for this journal club (optional reading) (sorry, url’s don’t work any more)

  • Kingman 1982a On the Genealogy of Large Populations, J. F. C. Kingman, Journal of Applied Probability, 19, 1982
  • Kingman 1982b The Coalescent, J. F. C. Kingman, Stochastic Systems and their Applications, 13, 1982

/home/ftp/pub/www/mackay/secret/paper_760coalescent.pdf

This talk is part of the Machine Learning Journal Club series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.

 

© 2006-2020 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity