University of Cambridge > > Machine Learning Reading Group @ CUED > Completely Random Measures

Completely Random Measures

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

If you have a question about this talk, please contact Shakir Mohamed.

Completely random measures are distributions over measures that assign independent masses to disjoint subsets. Examples include the beta process, gamma process and stable process.

We will cover infinite divisibility, completely random measures, normalized random measures, and neutral-to-the-right processes.

A good general reference for the material covered is Lijoi and PrĂ¼nster (2010) Models beyond the Dirichlet process. In Hjort et al (eds), Bayesian Nonparametrics, CUP . – available here:

This talk is part of the Machine Learning Reading Group @ CUED series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.


© 2006-2024, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity