Meta-Surrogate Benchmarking for Hyperparameter Optimization

NeurIPS 2019 Aaron KleinZhenwen DaiFrank HutterNeil LawrenceJavier Gonzalez

Despite the recent progress in hyperparameter optimization (HPO), available benchmarks that resemble real-world scenarios consist of a few and very large problem instances that are expensive to solve. This blocks researchers and practitioners not only from systematically running large-scale comparisons that are needed to draw statistically significant results but also from reproducing experiments that were conducted before... (read more)

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