SpringerBriefs in Optimization - Bayesian Optimization and Data Science
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Published By Springer International Publishing

9783030244934, 9783030244941

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SpringerBriefs in Optimization - Bayesian Optimization and Data Science ◽

10.1007/978-3-030-24494-1_6 ◽

2019 ◽

pp. 97-109

Author(s):

Francesco Archetti ◽

Antonio Candelieri

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Automated Machine Learning and Bayesian Optimization

SpringerBriefs in Optimization - Bayesian Optimization and Data Science ◽

10.1007/978-3-030-24494-1_1 ◽

2019 ◽

pp. 1-18

Author(s):

Francesco Archetti ◽

Antonio Candelieri

Keyword(s):

Machine Learning ◽

Bayesian Optimization ◽

Automated Machine Learning

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Selected Applications

SpringerBriefs in Optimization - Bayesian Optimization and Data Science ◽

10.1007/978-3-030-24494-1_7 ◽

2019 ◽

pp. 111-126

Author(s):

Francesco Archetti ◽

Antonio Candelieri

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From Global Optimization to Optimal Learning

SpringerBriefs in Optimization - Bayesian Optimization and Data Science ◽

10.1007/978-3-030-24494-1_2 ◽

2019 ◽

pp. 19-35

Author(s):

Francesco Archetti ◽

Antonio Candelieri

Keyword(s):

Global Optimization ◽

Optimal Learning

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Exotic Bayesian Optimization

SpringerBriefs in Optimization - Bayesian Optimization and Data Science ◽

10.1007/978-3-030-24494-1_5 ◽

2019 ◽

pp. 73-96

Author(s):

Francesco Archetti ◽

Antonio Candelieri

Keyword(s):

Bayesian Optimization

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The Acquisition Function

SpringerBriefs in Optimization - Bayesian Optimization and Data Science ◽

10.1007/978-3-030-24494-1_4 ◽

2019 ◽

pp. 57-72

Author(s):

Francesco Archetti ◽

Antonio Candelieri

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The Surrogate Model

SpringerBriefs in Optimization - Bayesian Optimization and Data Science ◽

10.1007/978-3-030-24494-1_3 ◽

2019 ◽

pp. 37-56

Author(s):

Francesco Archetti ◽

Antonio Candelieri

Keyword(s):

Surrogate Model

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