BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:&quot\;An Unbiased and Scalable Monte Carlo Method for Bayesian In
 ference for Big Data&quot\; - Dr Murray Pollock\, University of Warwick
DTSTART:20160112T143000Z
DTEND:20160112T153000Z
UID:TALK63425@talks.cam.ac.uk
CONTACT:Alison Quenault
DESCRIPTION:Abstract: This talk will introduce novel methodology for explo
 ring posterior distributions by modifying methodology for exactly (without
  error) simulating diffusion sample paths - the Scalable Langevin Exact Al
 gorithm (ScaLE). This new method has remarkably good scalability propertie
 s (among other interesting properties) as the size of the data set increas
 es (it has sub-linear cost\, and potentially no cost)\, and therefore is a
  natural candidate for ``Big Data'' inference.
LOCATION:Large  Seminar Room\, 1st Floor\, Institute of Public Health\, Un
 iversity Forvie Site\, Robinson Way\, Cambridge
END:VEVENT
END:VCALENDAR