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  5. Exploring Bayesian optimization
 
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Exploring Bayesian optimization

Source
Distill
Date Issued
2020-05-01
Author(s)
Agnihotri, Apoorv
Batra, Nipun
DOI
10.23915/distill.00026
Volume
vol. 5
Issue
no. 5
Abstract
Many modern machine learning algorithms have a large number of hyperparameters. To effectively use these algorithms, we need to pick good hyperparameter values. 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.
Publication link
https://doi.org/10.23915/distill.00026
URI
https://d8.irins.org/handle/IITG2025/30148
Subjects
Mining Gold
Gold Distribution
Bayesian Optimization
Acquisition Functions
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