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Aug, 2019
关于评估贝叶斯优化自身超参数影响的研究
Towards Assessing the Impact of Bayesian Optimization's Own Hyperparameters
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Marius Lindauer, Matthias Feurer, Katharina Eggensperger, André Biedenkapp, Frank Hutter
TL;DR
本文研究贝叶斯优化在超参数优化中的应用，发现优化BO的超参数可以提高BO方法在各种基准测试中的的表现，优化后的BO调参效果在其他相似或不同领域的问题上有良好的推广性，并指出了最重要的BO超参数。
Abstract
bayesian optimization
(BO) is a common approach for
hyperparameter optimization
(HPO) in automated machine learning. Although it is well-accepted that HPO is crucial to obtain well-performing
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