Bayesian Optimization Library
=======================
The bayesian optimization algorithm is a surrogate-based optimizer that can
optimize expensive black-box functions. This implementation is specifically
tuned to optimize deel neural networks. It is able to handle paralell
evaluations on multiple GPUs, and can use a Random Forest surrogate model.
For additional details see our paper: <https://coming_soon>`_.
=======================
The bayesian optimization algorithm is a surrogate-based optimizer that can
optimize expensive black-box functions. This implementation is specifically
tuned to optimize deel neural networks. It is able to handle paralell
evaluations on multiple GPUs, and can use a Random Forest surrogate model.
For additional details see our paper: <https://coming_soon>`_.
1 maintainer
Release files for ParallelBayesOpt 0.9.2
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Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| ParallelBayesOpt-0.9.2.tar.gz | 13.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| ParallelBayesOpt-0.9.2-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details |
Total release size: 25.4 kB
Release files / ParallelBayesOpt-0.9.2.tar.gz
| Download URL | ParallelBayesOpt-0.9.2.tar.gz |
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| Size | 13.2 kB |
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Release files / ParallelBayesOpt-0.9.2-py2.py3-none-any.whl
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| Size | 12.2 kB |
| Tags | Python 2 Python 3 |
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