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 - and practitioners from other fields - wishing to harness the power of Bayesian optimization. Publisher: Cambridge University Press Author(s): Roman (Washington University in St Louis) Garnett Illustration(s): Worked examples or Exercises Number of pages: 358 Publication date: 2023 Dimensions: 259 x 211 x 24 Cover type: Hardback