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Bayesian Optimization Library with GPU support

Project description

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>`_.

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