PyXAB -- A Python Library for $\mathcal{X}$-Armed Bandit and Online Blackbox Optimization Algorithms

Wenjie Li, Haoze Li, Jean Honorio, Qifan Song
3/7/2023
stat.MLcs.AIcs.LG

Official code: WilliamLwj/PyXAB (127 stars, MIT, last commit 2024-10-24).

Abstract

We introduce a Python open-source library for $\mathcal{X}$-armed bandit and online blackbox optimization named PyXAB. PyXAB contains the implementations for more than 10 $\mathcal{X}$-armed bandit algorithms, such as HOO, StoSOO, HCT, and the most recent works GPO and VHCT. PyXAB also provides the most commonly-used synthetic objectives to evaluate the performance of different algorithms and the various choices of the hierarchical partitions on the parameter space. The online documentation for PyXAB includes clear instructions for installation, straight-forward examples, detailed feature descriptions, and a complete reference of the API. PyXAB is released under the MIT license in order to encourage both academic and industrial usage. The library can be directly installed from PyPI with its source code available at https://github.com/WilliamLwj/PyXAB

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Code Implementations(1)

WilliamLwj/PyXABOfficial100%
MIT

PyXAB - A Python Library for X-Armed Bandit and Online Blackbox Optimization Algorithms

12732PythonMar 16, 20221 years agoMIT
algorithmautomlbandit-algorithmsblackbox-optimizationcontinuous-armed-bandit+11 more

Cite this paper

@article{li2023pyxab,
  title  = {PyXAB -- A Python Library for $\mathcal{X}$-Armed Bandit and Online Blackbox Optimization Algorithms},
  author = {Wenjie Li and Haoze Li and Jean Honorio and Qifan Song},
  year   = {2023},
  eprint = {2303.04030},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2303.04030v1}
}

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