Connectionists: CFP: NIPS 2015 Workshop on Bayesian Optimization

[Bobak Shahriari]

NIPS 2015 Workshop on Bayesian Optimization
Montreal, QC, Canada, 12 December 2015
bayesopt.github.io

Workshop overview:
The NIPS Workshop on Bayesian Optimization is calling for contributions on
theoretical models, empirical studies, and applications of Bayesian
optimization.

This year will focus on scaling existing approaches to larger evaluation
budgets, higher-dimensional search spaces, and more complex input spaces.
While the computational complexity of common probabilistic regression
models used in Bayesian optimization have confined it to relatively
low-dimensional problems and small evaluation budgets, there have, in
recent years, been several advances in scaling these probabilistic models
to more demanding application domains. Furthermore, many applications of
Bayesian optimization only make sense when considering concurrent
evaluations, which departs from the traditional, strictly sequential
Bayesian optimization framework. Recent theoretical and practical efforts
have addressed the mini-batch, or parallel, evaluation framework. Finally,
as always, We also welcome challenge papers on possible applications or
datasets.

Important dates:
Submission deadline: October 23rd, 2015
Notification: November 2nd, 2015
Camera ready: December 4th, 2015

Invited speakers (confirmed):
Zoubin Ghahramani (University of Cambridge)
Andreas Krause (ETH Zurich)
Jeff Schneider (Carnegie Mellon University)
Marc Deisenroth (Imperial College London)

Further details and instructions:
See also the workshop website <http://bayesopt.github.io/index.html> for
more details and submission instructions. Submissions can be made through
cmt.research.microsoft.com/BO2015.

Organizers:
Nando de Freitas (Google DeepMind/Oxford University)
Ryan Adams (Harvard University)
Bobak Shahriari (University of British Columbia)
Roberto Calandra (TU Darmstadt)
Amar Shah (University of Cambridge)

Best,

Bobak
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