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>`_.
=======================
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>`_.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
ParallelBayesOpt-0.9.2.tar.gz
(13.2 kB
view details)
Built Distribution
File details
Details for the file ParallelBayesOpt-0.9.2.tar.gz
.
File metadata
- Download URL: ParallelBayesOpt-0.9.2.tar.gz
- Upload date:
- Size: 13.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 |
ecafa6cf7a2b653b4b3d3a3b27d42c7badfcc02034fa01c8ebf4d8c6d6bfbef6
|
|
MD5 |
abac1685e4b42e8b1d3c8ce3f733990b
|
|
BLAKE2b-256 |
3655589d869f56a400cf9beabeb826180f91f2afd6cb5515d9b4047a09f2e563
|
File details
Details for the file ParallelBayesOpt-0.9.2-py2.py3-none-any.whl
.
File metadata
- Download URL: ParallelBayesOpt-0.9.2-py2.py3-none-any.whl
- Upload date:
- Size: 12.2 kB
- Tags: Python 2, Python 3
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 |
115153b32799a40585ee23fcecf7cefe162414c8cf8d1349b6e530683f794b19
|
|
MD5 |
9a662fe056992536e1cc96ac7d72a0cb
|
|
BLAKE2b-256 |
c135cc230e26b8f5402b207c8e662f701cdec1f9e60dd43432c908081a088773
|