Re:USGS uses machine learning to show large lithium potentia...
by youoy on Wednesday October 23, 2024 @04:14AM
(#41922930)
The drilling and active learning part reminded me of this very nice article on Bayesian Optimization from Distill publication [0].
They explain it for selecting the hyper parameters for ML models:
> In this article, we talk about Bayesian Optimization, a suite of techniques often used to tune hyperparameters. More generally, Bayesian Optimization can be used to optimize any black-box function.
But the example at the beginning of the article is mining gold:
> Let us start with the example of gold mining. Our goal is to mine for gold in an unknown land 1 . For now, we assume that the gold is distributed about a line. We want to find the location along this line with the maximum gold while only drilling a few times (as drilling is expensive).
They explain it for selecting the hyper parameters for ML models:
> In this article, we talk about Bayesian Optimization, a suite of techniques often used to tune hyperparameters. More generally, Bayesian Optimization can be used to optimize any black-box function.
But the example at the beginning of the article is mining gold:
> Let us start with the example of gold mining. Our goal is to mine for gold in an unknown land 1 . For now, we assume that the gold is distributed about a line. We want to find the location along this line with the maximum gold while only drilling a few times (as drilling is expensive).
[0] https://distill.pub/2020/bayesian-optimization/