nuvard / bbo-challenge-jetbrains-research

Code for Solving Black-Box Optimization Challenge via Learning Search Space Partition for Local Bayesian Optimization.

JetBrains Research's Solution for Black-Box Optimization Challenge

This is the code for our solution to the NeurIPS 2020 Black-Box Optimization Challenge.

Our solution is described in the "Solving Black-Box Optimization Challenge via Learning Search Space Partition for Local Bayesian Optimization" paper.

Final Results

Our approach scored 92.509 in the finals and ranked 3rd overall!

Team Members

• Mikita Sazanovich (github: @niksaz)
• Anastasiya Nikolskaya (github: @nuvard)
• Yury Belousov (github: @bruce-willis)
• Aleksei Shpilman

Citing us

The paper is available at: https://arxiv.org/pdf/2012.10335.pdf.

If you want to cite this code, please use the following:

@misc{sazanovich2020solving,
      title={Solving Black-Box Optimization Challenge via Learning Search Space Partition for Local Bayesian Optimization}, 
      author={Mikita Sazanovich and Anastasiya Nikolskaya and Yury Belousov and Aleksei Shpilman},
      year={2020},
      eprint={2012.10335},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}

License

Our implementation is released under Apache License 2.0 license except for the code derived from TuRBO.