Bayesian optimization for sklearn

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https://github.com/JasperSnoek/spearmint

http://people.seas.harvard.edu/~jsnoek/software.html

http://fastml.com/tuning-hyperparams-automatically-with-spearmint/

http://www.johnmyleswhite.com/notebook/2012/07/21/automatic-hyperparameter-tuning-methods/

https://github.com/fmfn/Bayesian-Optimization-with-Gaussian-Processes

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Hyperparameter Opt 101 (Bergstra) https://www.youtube.com/watch?v=tteE_Vtmrv4

Longer talk on HP opt (Bergstra) https://www.youtube.com/watch?v=LlNI5UMDzzQ

Hyperopt Scipy2013 (Bergstra) https://www.youtube.com/watch?v=Mp1xnPfE4PY

Random Search (Bergstra) http://jmlr.org/papers/volume13/bergstra12a/bergstra12a.pdf

Algorithms for Hyperparameter Optimization (Bergstra) http://papers.nips.cc/paper/4443-algorithms-for-hyper-parameter-optimization.pdf

Implementations of Algorithms For Hyperparmater Optimization http://www.cs.ubc.ca/~hutter/nips2011workshop/papers_and_posters/Bergstra-abstract.pdf

Making A Science of Model Search (Bergstra) http://jmlr.org/proceedings/papers/v28/bergstra13.pdf

Bayesian Optimization (Snoek) https://www.youtube.com/watch?v=a79klpzaPgY

Machine Learning for Predictive AutoTuning (Bergstra) http://www.rowland.org/rjf/cox/pdfs/inpar2012.pdf

Towards an Empirical Foundation for Assesing Bayesian Optimization http://www.cs.ubc.ca/~kevinlb/papers/2013-BayesOpt-Hyperparameters.pdf

Challenges in Repr. Learning http://arxiv.org/pdf/1307.0414.pdf

GP Optimization https://www.youtube.com/watch?v=vz3D36VXefI

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Nice, basic GP code http://nbviewer.ipython.org/github/fonnesbeck/Bios366/blob/master/notebooks/Section5_1-Gaussian-Processes.ipynb

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Talk by James http://vip.uwaterloo.ca/files/news-attachments/Bergstra%20Talk.pdf

Paper from NdeF http://www.cs.ubc.ca/~nando/540-2013/projects/p53.pdf

A simple project using GP https://github.com/fmfn/Bayesian-Optimization-with-Gaussian-Processes

NdeF again: http://arxiv.org/pdf/1012.2599v1.pdf