Bayesian optimization: Difference between revisions

Revision as of 13:07, 20 September 2024

Revision as of 13:08, 20 September 2024

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| isbn=978-1107163447

| url = https://www.probabilistic-numerics.org/assets/ProbabilisticNumerics.pdf

}}</ref> that does not assume any functional forms. It is usually employed to optimize expensive-to-evaluate functions. With the rise of [[artificial intelligence]] innovation in the 21st century, Bayesian optimizations have found prominent use in [[machine learning]] hyperparameterproblems, optimizationfor problemsoptimising hyperparameter values.<ref>{{cite journal |first=Jasper|last=Snoek |title=Practical Bayesian Optimization of Machine Learning Algorithms |journal=Advances in Neural Information Processing Systems 25 (NIPS 2012) |year=2012}}</ref>

==History==