Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Test GP-based optimization #13

Closed
arogozhnikov opened this issue Jul 16, 2015 · 2 comments
Closed

Test GP-based optimization #13

arogozhnikov opened this issue Jul 16, 2015 · 2 comments
Assignees
Milestone

Comments

@arogozhnikov
Copy link
Contributor

Build an additional test that GaussianProcess optimization works fine.

For batch optimization, probably some improvement is possible, which also minimizes an overall variance as well as looking for most optimal model. (Need to check if some well-tested implementation exists).

Sklearn's gaussian processes don't support variance of measurements, which probably could improve search.

@arogozhnikov arogozhnikov self-assigned this Jul 16, 2015
@arogozhnikov arogozhnikov added this to the 0.6.3 milestone Jul 16, 2015
@arogozhnikov
Copy link
Contributor Author

related link:
http://arxiv.org/pdf/1206.2944v2.pdf

@arogozhnikov
Copy link
Contributor Author

Currently simple GP-optimization is demonstrated in https://github.com/yandex/rep/blob/master/howto/03-howto-gridsearch.ipynb via RegressionOptimization, but maybe some specific solutions will be added later.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Projects
None yet
Development

No branches or pull requests

1 participant