NIPS 2012 Workshop on Bayesian Optimization and Decision Making


NIPS 2012 Workshop on

Bayesian Optimization & Decision Making




December 7th 2012, Lake Tahoe, Nevada, USA

  Home Submissions Program Committee Schedule  

Recent years have brought substantial advances in sequential decision making under uncertainty. These advances have occurred in many different communities, including several subfields of computer science, statistics, and electrical/mechanical/chemical engineering. While these communities are essentially trying to solve the same problem, they develop rather independently, using different terminology: Bayesian  optimization, experimental design, bandits, active sensing, personalized recommender systems, automatic algorithm configuration, reinforcement learning, and so on. Some communities focus more on theoretical aspects while others' expertise is on real-world applications. This workshop aims to bring researchers from these communities together to facilitate cross-fertilization by discussing challenges, findings, and sharing data. This workshop follows last year's NIPS workshop "Bayesian optimization, experimental design and bandits: Theory and applications". This year we plan to focus somewhat more on real-world applications, to bridge the gap between theory and practice.

Important Dates: 

  • Papers Due:       September 16th
    (Extended to September 23rd 2012)
  • Notification :     October 14th 2012
  • Camera Ready: October 25th 2012
  • Workshop:         December 7th 2012

Latest News:

  • Nov 24th: The program details are available in the website now.
  • Oct 18th: List of the accepted papers are available in the website now.
  • Sept 16th: The paper submission deadline has been extended to Sept 23rd .
  • Aug 22nd: Here is the link to the workshop call for paper.
  • Aug 22nd: The website is up.






  • Bayesian optimization
  • Sequential experimental design and decision making
  • Applications, e.g., automatic parameter tuning, active sensing, robotics
  • Related areas: active learning, reinforcement learning, bandits, etc
We welcome contributions on theoretical models, empirical studies, and applications of the above. We also welcome challenge papers on possible applications or datasets.
  Invited Speakers (Confirmed)
  Industrial Panel Discussion
In addition to the invited speakers, the following people will participate the industrial panel discussion:
  • Javad Azimi (Research Scientist, InsightsOne Inc)
  • Roman Garnett (Postdoctoral Researcher, Carnegie Mellon University)
  • Frank Hutter (Postdoctoral Researcher, University of British Columbia)
  • Shakir Mohamed (Postdoctoral Researcher, University of British Columbia)