Bayesian Optimization and Data Science

• Κύριοι συγγραφείς: Archetti, Francesco (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Candelieri, Antonio (http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Έκδοση: 1st ed. 2019.
• Σειρά: SpringerBriefs in Optimization,
• Θέματα: Operations research.; Management science.; Machine learning.; Computer software.; Statistics .; Operations Research, Management Science.; Machine Learning.; Mathematical Software.; Bayesian Inference.

This volume brings together the main results in the field of Bayesian Optimization (BO), focusing on the last ten years and showing how, on the basic framework, new methods have been specialized to solve emerging problems from machine learning, artificial intelligence, and system optimization. It al...

Πίνακας περιεχομένων:

• 1. Automated Machine Learning and Bayesian Optimization
• 2. From Global Optimization to Optimal Learning
• 3. The Surrogate Model
• 4. The Acquisition Function
• 5. Exotic BO
• 6. Software Resources
• 7. Selected Applications.