NIPS 2010 workshop: Monte Carlo Methods for Bayesian Inference in Modern Day Applications
*** Deadline: October 31, for 1-page abstracts.
—————————————————————————
NIPS 2010 workshop
Monte Carlo Methods for Bayesian Inference in Modern Day Applications
http://montecarlo.wikidot.com/
http://nips.cc/
December 10, 2010
Whistler, Canada. Westin Resort and Spa and Hilton Resort and Spa
Sponsored by the PASCAL2 EU Network of Excellence
—————————————————————————
We invite submissions on Monte Carlo methods and their practical
application. Particularly welcome are “tricks of the trade” and “war
stories” that might not make it into conventional publications.
Submissions are solicited both from researchers developing new
methodology and from practitioners using established techniques.
Send poster abstracts of up to one page to
montecarlo-nips2010(at)cs.toronto.edu
by Oct 31, 2010. Use the NIPS style file with no anonymity. We will
notify acceptances by Nov 4, before the NIPS early registration
deadline.
We intend to invite key contributions from the workshop to submit full
papers to a JMLR W&CP issue to appear in the new year.
We also invite contributions to the wiki, including suggested readings
and discussion topics:
http://montecarlo.wikidot.com/
The organizers:
Ryan Prescott Adams, http://www.cs.toronto.edu/~rpa/
Mark Girolami, http://www.dcs.gla.ac.uk/inference/
Iain Murray, http://homepages.inf.ed.ac.uk/imurray2/
Confirmed invited speakers:
Derek Bingham
Julien Cornebise
Arnaud Doucet
Andrew McCallum
Yee-Whye Teh
Max Welling
Workshop description:
Monte Carlo methods have been the dominant form of approximate inference for
Bayesian statistics over the last couple of decades. Monte Carlo methods are
interesting as a technical topic of research in themselves, as well as enjoying
widespread practical use. In a diverse number of application areas Monte Carlo
methods have enabled Bayesian inference over classes of statistical models which
previously would have been infeasible. Despite this broad and sustained
attention, it is often still far from clear how best to set up a Monte Carlo
method for a given problem, how to diagnose if it is working well, and how to
improve under-performing methods. The impact of these issues is even more
pronounced with new emerging applications. This workshop is aimed equally at
practitioners and core Monte Carlo researchers. For practitioners we hope to
identify what properties of applications are important for selecting, running
and checking a Monte Carlo algorithm. Monte Carlo methods are applied to a broad
variety of problems. The workshop aims to identify and explore what properties
of these disparate areas are important to think about when applying Monte Carlo
methods.
We look forward to seeing you in Whistler this December!
