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May, 2023
使用符合量化回归优化超参数
Optimizing Hyperparameters with Conformal Quantile Regression
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David Salinas, Jacek Golebiowski, Aaron Klein, Matthias Seeger, Cedric Archambeau
TL;DR
本文提出了一种利用基于置信度的分位数回归的超参数优化算法，相较于传统高斯过程模型，它能够更加真实和鲁棒地建模目标函数，加速超参数优化过程，并在多保真度场景下比传统方法表现更好。
Abstract
Many state-of-the-art
hyperparameter optimization
(HPO) algorithms rely on
model-based optimizers
that learn surrogate models of the target function to guide the search.
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