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Re:A Practical Guide to Hyperparameter Optimization by ArtWomb on Thursday April 18, 2019 @07:59AM (#19690311)
More essential background on Bayesian optimization in AutoML's HyperTune

https://cloud.google.com/blog/products/gcp/hyperparameter-tu...

Re:A Practical Guide to Hyperparameter Optimization by Zephyr314 on Thursday April 18, 2019 @12:58PM (#19692636)
There are also several papers and blog posts diving into details and tradeoffs of different Bayesian optimization approaches and components here [0]. Example: Covariance Kernels for Avoiding Boundaries [1]

[0]: https://sigopt.com/research/

[1]: https://sigopt.com/blog/covariance-kernels-for-avoiding-boun...

Re:A Practical Guide to Hyperparameter Optimization by manneshiva on Thursday April 18, 2019 @08:09AM (#19690370)
Even Facebook uses Bayesian Optimization for tuning the parameters of some of its online systems (like its internal ranking system): https://research.fb.com/efficient-tuning-of-online-systems-u...