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Multiple Information Source Bayesian Optimization
Engelsk
Bogcover for Multiple Information Source Bayesian Optimization af Antonio Candelieri, Francesco Archetti, Andrea Ponti, 9783031979644
Specifikationer
Sprog:
Engelsk
Sider:
99
ISBN-13:
9783031979644
Indbinding:
Paperback
ISBN-10:
3031979648
Udg. Dato:
31 aug 2025
Størrelse i cm:
23,5 x 15,5
Oplagsdato:
31 aug 2025

Multiple Information Source Bayesian Optimization

Engelsk
Paperback 2025
Format:

Bog beskrivelse
The book provides a comprehensive review of multiple information sources and multi-fidelity Bayesian optimization, specifically focusing on the novel "Augmented Gaussian Process” methodology. The book is important to clarify the relations and the important differences in using multi-fidelity or multiple information source approaches for solving real-world problems. Choosing the most appropriate strategy, depending on the specific problem features, ensures the success of the final solution. The book also offers an overview of available software tools: in particular it presents two implementations of the Augmented Gaussian Process-based Multiple Information Source Bayesian Optimization, one in Python -- and available as a development branch in BoTorch -- and finally, a comparative analysis against other available multi-fidelity and multiple information sources optimization tools is presented, considering both test problems and real-world applications. The book will be useful to two main audiences:1. PhD candidates in Computer Science, Artificial Intelligence, Machine Learning, and Optimization2. Researchers from academia and industry who want to implement effective and efficient procedures for designing experiments and optimizing computationally expensive experiments in domains like engineering design, material science, and biotechnology.  
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Specifikationer
Sprog:
Engelsk
Sider:
99
ISBN-13:
9783031979644
Indbinding:
Paperback
ISBN-10:
3031979648
Udg. Dato:
31 aug 2025
Størrelse i cm:
23,5 x 15,5
Oplagsdato:
31 aug 2025
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