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Feb, 2022
基于灰盒动态优化的深度学习超参数高效优化
Dynamic and Efficient Gray-Box Hyperparameter Optimization for Deep Learning
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Martin Wistuba, Arlind Kadra, Josif Grabocka
TL;DR
介绍了一种名为DyHPO的灰箱超参数优化方法,它能够学习动态决定下一个尝试哪个配置和预算。通过50个数据集和各种神经网络的大规模实验,我们证明了DyHPO比最先进的超参数优化基线具有显着的优越性。
Abstract
gray-box hyperparameter optimization
techniques have recently emerged as a promising direction for tuning
deep learning
methods. In this work, we introduce
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