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CALL FOR CONTRIBUTIONS
NIPS workshop on Bayesian optimization, experimental design and bandits: Theory and applications
Sierra Nevada, Spain, December 16 or 17, 2011
web: http://www.cs.ubc.ca/~hutter/nips2011workshop/index.html
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Important Dates:
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* Submission of extended abstracts: September 23, 2011 (later submission might not be considered for review)
* Notification of acceptance: October 15, 2011
* Final versions of accepted papers due: November 29, 2011
* Workshop date: December 16 or 17, 2011

Overview:
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Recently, we have witnessed many important advances in learning approaches for sequential decision making. These advances have occurred in different communities, who refer to the problem using different terminology: Bayesian optimization, experimental design, bandits (x-armed bandits, contextual bandits, Gaussian process bandits), active sensing, personalized recommender systems, automatic algorithm configuration, reinforcement learning and so on.
These communities tend to use different methodologies too. Some focus more on practical performance while others are more concerned with theoretical aspects of the problem. As a result, they have derived and engineered a diverse range of methods for trading off exploration and exploitation in learning, For these reasons, it is timely and important to bring these communities together to identify differences and commonalities, to propose common benchmarks, to review the many practical applications (interactive user interfaces, automatic tuning of parameters and architectures, robotics, recommender systems, active vision, and more), to narrow the gap between theory and practice and to identify strategies for attacking high-dimensionality.

Invited speakers (confirmed):
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* Andreas Krause, ETH Zurich and Caltech
* Csaba Szepesvari, University of Alberta
* Remi Munos, INRIA Lille - Nord Europe
* Louis Dorard, University College London

Topics of interest:
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* Bayesian optimization
* Sequential experimental design
* Bandits
* Exploration-exploitation trade-off

We welcome contributions on theoretical models, empirical studies, and applications of the above. The list is not exhaustive, and we also welcome submissions on highly related topics.

Submission instructions:
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Submissions must be in the NIPS 2011 format, but with a maximum of 4 pages (excluding references). Accepted papers will be made available online at the workshop website but the workshop proceedings can be considered non-archival.
Paper submissions should be sent by email in PDF or PS file format to nips2011.bayesopt@gmail.com with a subject line of "NIPS-BayesOpt 2011: XXX", where "XXX" is the title of the submission.


Organizers:
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* Nando de Freitas, Professor of Machine Learning, University of British Columbia
* Roman Garnett, Postdoctoral Researcher, Carnegie Mellon University
* Frank Hutter, Postdoctoral Researcher, University of British Columbia
* Michael A Osborne, Postdoctoral Researcher, University of Oxford

Contact:
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mailto: nips2011.bayesopt@gmail.com