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Should we consider adding bayesmark to the benchmarking suite
The bayesmark package is another wrapper hyper parameter tuning library. We can add this to our benchmarking suite. Per their documentation, they wrap around:
The builtin optimizers are wrappers on the following projects:
HyperOpt
Nevergrad
OpenTuner
PySOT
Scikit-optimize
https://github.com/uber/bayesmark/
And we already benchmark against HyperOpt. Note that OpenTuner is a previous package developed at MIT in 2014.
We have in the past tried Nevergrad. Alternatively, we can just add Nevergrad, Scitkit-optimize and PySOT individually.