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Über den Autor
Roman Garnett is Associate Professor at Washington University in St. Louis. He has been a leader in the Bayesian optimization community since 2011, when he co-founded a long-running workshop on the subject at the NeurIPS conference. His research focus is developing Bayesian methods - including Bayesian optimization - for automating scientific discovery, an effort supported by an NSF CAREER award.
Inhaltsverzeichnis
Notation; 1. Introduction; 2. Gaussian processes; 3. Modeling with Gaussian processes; 4. Model assessment, selection, and averaging; 5. Decision theory for optimization; 6. Utility functions for optimization; 7. Common Bayesian optimization policies; 8. Computing policies with Gaussian processes; 9. Implementation; 10. Theoretical analysis; 11. Extensions and related settings; 12. A brief history of Bayesian optimization; A. The Gaussian distribution; B. Methods for approximate Bayesian inference; C. Gradients; D. Annotated bibliography of applications; References; Index.
Details
Erscheinungsjahr: 2023
Genre: Importe, Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Inhalt: Gebunden
ISBN-13: 9781108425780
ISBN-10: 110842578X
Sprache: Englisch
Einband: Gebunden
Autor: Garnett, Roman
Hersteller: Cambridge University Press
Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, D-36244 Bad Hersfeld, gpsr@libri.de
Maße: 260 x 208 x 25 mm
Von/Mit: Roman Garnett
Erscheinungsdatum: 09.02.2023
Gewicht: 1,027 kg
Artikel-ID: 122091923

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