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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 |
Ausstattung / Beilage: | HC gerader Rücken kaschiert |
Einband: | Gebunden |
Autor: | Garnett, Roman |
Hersteller: | Cambridge University Press |
Verantwortliche Person für die EU: | Books on Demand GmbH, In de Tarpen 42, D-22848 Norderstedt, info@bod.de |
Maße: | 260 x 208 x 25 mm |
Von/Mit: | Roman Garnett |
Erscheinungsdatum: | 09.02.2023 |
Gewicht: | 1,029 kg |
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 |
Ausstattung / Beilage: | HC gerader Rücken kaschiert |
Einband: | Gebunden |
Autor: | Garnett, Roman |
Hersteller: | Cambridge University Press |
Verantwortliche Person für die EU: | Books on Demand GmbH, In de Tarpen 42, D-22848 Norderstedt, info@bod.de |
Maße: | 260 x 208 x 25 mm |
Von/Mit: | Roman Garnett |
Erscheinungsdatum: | 09.02.2023 |
Gewicht: | 1,029 kg |
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