Roman Garnett (Washington University in St Louis)

Gebundenes Buch

Bayesian Optimization

Beschreibung

Bayesian optimization is a methodology that has proven success in the sciences, engineering, and beyond for optimizing expensive objective functions. This self-contained text targets graduate students and researchers in machine learning and statistics â and practitioners from other fields â wishing to harness the power of Bayesian optimization.

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.

Produktdetails

• Verlag: Cambridge University Press
• Seitenzahl: 376
• Erscheinungstermin: 9. Februar 2023
• Englisch
• Abmessung: 260mm x 208mm x 25mm
• Gewicht: 992g
• ISBN-13: 9781108425780
• ISBN-10: 110842578X
• Artikelnr.: 64298271