Hi Simon, Thanks for sharing. In my opinion, apart from discretizing the search space, the N-Tuple system takes a very intuitive approach to hyper-parameter optimization. The github repo readme notes you're working on an extended version to handle continuous parameters, what's your general approach to that issue?
Thanks, -Chaz On Sun, Jan 13, 2019 at 11:51 AM Simon Lucas <simon.lu...@qmul.ac.uk> wrote: > Hi all, > > > > The N-Tuple Bandit Evolutionary Algorithm aims > > to provide sample-efficient optimisation, especially > > for noisy problems. > > > > Software available in Java and Python: > > > > https://github.com/SimonLucas/ntbea > > > > It also provides stats on the value of each parameter setting > > and combinations of settings. > > > > Best wishes, > > > > Simon > > > > > > -- > > Simon Lucas > > Professor of Artificial Intelligence > > Head of School > > Electronic Engineering and Computer Science > > Queen Mary University of London > > > > > > > _______________________________________________ > Computer-go mailing list > Computer-go@computer-go.org > http://computer-go.org/mailman/listinfo/computer-go
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