-**This code is still in beta.** The release code will appear in http://bitbucket.org/rmcantin/bayesopt
+**This repository is a mirror.** The actual repository is http://bitbucket.org/rmcantin/bayesopt
+If you have cloned this repository, you can change the address in the .hg/hgrc file in your local repository.
For any question, comment or to be informed about the release time, please subscribe to the [[https://groups.google.com/d/forum/bayesopt-discussion|discussion list]]
-This is an efficient, C++ implementation of several Bayesian optimization
-algorithms. See References for some of the papers.
-It combines the use of a stochastic process as a surrogate function
-with some "active learning" criterion to find the optimum of an "arbitrary"
-function using very few iterations. It can also be used for sequential experimental
-design and stochastic bandits by selecting the adequate criterion.
-Using old C++ standards (C++98), it can be used with many compilers in Windows,
-Linux, Mac OS. There are APIs for C/C++, Python and Matlab/Octave.
-**Important:** This code is free to use. However, if you are using, or plan to use, the library, //specially if it is for research or academic purposes//, please send me an [[mailto:email@example.com|email]] with your name, institution and a brief description of your interest for this code (one or two lines).
-If you use BayesOpt in work that leads to a publication, we would appreciate it if you would kindly cite BayesOpt in your manuscript. Cite BayesOpt as something like:
-* Ruben Martinez-Cantin, **BayesOpt: a toolbox for nonlinear-optimization, experimental design and stochastic bandits, http://bitbucket.org/rmcantin/bayesopt**
- Copyright (C) 2011-2012 Ruben Martinez-Cantin <firstname.lastname@example.org>
- BayesOpt is free software: you can redistribute it and/or modify it
- under the terms of the GNU General Public License as published by
- the Free Software Foundation, either version 3 of the License, or
- (at your option) any later version.
- BayesOpti is distributed in the hope that it will be useful, but
- WITHOUT ANY WARRANTY; without even the implied warranty of
- MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- GNU General Public License for more details.
- You should have received a copy of the GNU General Public License
- along with BayesOpt. If not, see <[[http://www.gnu.org/licenses/|http://www.gnu.org/licenses/]]>.