The First Workshop on Case Studies of Bayesian Statistics and Machine Learning will take place on October 16th and 17th, 2009 at Carnegie Mellon University, Pittsburgh, PA. The Workshop will focus applications of Bayesian statistics and Machine Learning to problems in science and technology. It will feature three different tracks: In-depth contributed presentations and discussions of substantial research, shorter presentations by young researchers and poster presentations. The workshop builds upon the Case Studies of Bayesian Statistics Workshop which was held at CMU for the last two decades. In conjunction with the workshop, the Department of Statistics' Eleventh Morris H DeGroot memorial lecture will be delivered by Professor Michael Jordan, University of California at Berkeley.
We are calling for abstracts for all three tracks. The first is for major case studies. Each presentation is expected to be delivered by both, the statistician / ML researcher and their collaborator(s) from the applied area. These presentations will be allocated a 3 hour slot and are expected to be detailed and represent long standing, successful collaborations. A detailed abstract (2-3 pages) from those interested in presenting one of these collaborations is due Monday, February 1, 2009. Abstracts should emphasize the scientific and technological background, and should clarify the extent to which the inferential work will address key components of the problems articulated. The second track is for 15-minute presentations by young researchers (students or those who completed PhD within the last five years). Abstracts for this track should be 1-2 pages and are due July 1. Abstracts should emphasize the scientific problems and how the statistical work solves the problems. Abstracts not selected for presentation would be considered for a poster session. In addition, we invite additional submissions for posters (1 page) which are due September 1, 2009. LONG ABSTRACTS DUE : FEBRUARY 1ST 2009 SHORT ABSTRACTS DUE : JULY 1ST 2009 POSTER ABSTRACTS DUE : SEPTEMBER 1ST Please submit abstracts via our webpage http://bayesml1.stat.cmu.edu/ which contains additional information, including abstracts of previous, successful case studies. For the past several meetings, the major case studies and certain others have appeared in the on-line (and free!) journal Bayesian Analysis. The Organizing Committee will explore a similar arrangement for this meeting's papers. If you have questions, please contact Jay Kadane at [email protected] or Ziv Bar-Joseph at [email protected]. Organizing Committee: Jay Kadane, Department of Statistics, CMU (program chair) Ziv Bar-Joseph, Machine Learning Department, CMU (program co-chair) David Blei, Computer Science Department, Princeton Merlise Clyde, Department of Statistics, Duke University Zoubin Ghahramani, Department of Engineering, Cambridge University David Heckerman, Microsoft Research Tommi Jaakkola, Electrical engineering and computer science, MIT Rob Kass, Department of Statistics, CMU Tony O'Hagan, Warwick University Dalene Stangl, Department of Statistics, Duke University _______________________________________________ uai mailing list [email protected] https://secure.engr.oregonstate.edu/mailman/listinfo/uai
