BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:Inference in the infinite relational model - Mikkel Schmidt (Techn
 ical University of Denmark)
DTSTART:20160727T133000Z
DTEND:20160727T140000Z
UID:TALK66861@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:The infinite relational model and similar related non-parametr
 ic mixture  models are very powerful for characterizing the structure in c
 omplex networks.  But (approximate) inference can be challenging\, especia
 lly for large networks\,  and both MCMC and variational inference is often
  hampered by local optima in the  posterior distribution. These issues are
  discussed in the context of learning a  high resolution parcellation of h
 uman brain structural connectivity network.
LOCATION:Seminar Room 1\, Newton Institute
END:VEVENT
END:VCALENDAR