OpenNMT Forum

Automating hyperparameter optimization

There are researchers who have discovered ways to leverage machine learning to optimize hyperparameter selection, as well as neural network design, such as mentioned here: Using Machine Learning to Optimize Machine Learning - AutoML.
Additional detail is provided in the links:
Large-Scale Evolution of Image Classifiers (2017)
and
Neural Architecture Search With Reinforcement Learning (2017)

Is there any interest in adopting these methods?

Has anyone tried using this library for hyperparameter optimization: https://github.com/hawk31/pyGPGO
?