HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO. Eggensperger, K., Müller, P., Mallik, N., Feurer, M., Sass, R., Klein, A., Awad, N., Lindauer, M., & Hutter, F. In Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2), 2021.
HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO [link]Paper  bibtex   
@inproceedings{nipsdb2021emmfskalh,
 author = {Katharina Eggensperger and Philipp M{\"u}ller and Neeratyoy Mallik and Matthias Feurer and Rene Sass and Aaron Klein and Noor Awad and Marius Lindauer and Frank Hutter},
 booktitle = {Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2)},
 keywords = {WP7,A-level},
 title = {{HPOB}ench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for {HPO}},
 url_paper = {https://openreview.net/pdf?id=1k4rJYEwda-},
 year = {2021}
}

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