BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:Infinite multiple relational models for complex networks - Mikkel 
 N. Schmidt (Technical University of Denmark / Cambridge)
DTSTART:20110127T140000Z
DTEND:20110127T153000Z
UID:TALK29119@talks.cam.ac.uk
CONTACT:Shakir Mohamed
DESCRIPTION:Learning latent structure in complex networks is an important 
 problem that has many application areas. In this talk I present a new non-
 parametric Bayesian multiple-membership latent feature model for networks.
  Contrary to existing multiple-membership models that scale quadratically 
 in the number of vertices\, the proposed model scales linearly in the numb
 er of links. I present an efficient split-merge inference procedure that s
 ignificantly outperform standard Gibbs sampling.
LOCATION:Engineering Department\, CBL Room 438
END:VEVENT
END:VCALENDAR