University of Cambridge > Talks.cam > Machine Learning @ CUED > Approaches to statistical modeling of network data

Approaches to statistical modeling of network data

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

If you have a question about this talk, please contact Zoubin Ghahramani.

General topic of my work is modeling of dynamic network data. Two contributions will be presented. At first I will speak about concepts and symmetry considerations underlying the models for network data. I will present a functional representation theorem for Markov exchangeable sequences. Next, I will describe an extension of latent distance model of Hoff and coauthors (JASA, 2002) to the case of dynamic network where the evolution of latent positions is assumed to follow an infinite hidden Markov model.

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

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.

 

© 2006-2017 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity