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Bayesian Optimization (Hardcover)
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Bayesian Optimization (Hardcover)
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Bayesian optimization is a methodology for optimizing expensive
objective functions that has proven success in the sciences,
engineering, and beyond. This timely text provides a self-contained
and comprehensive introduction to the subject, starting from
scratch and carefully developing all the key ideas along the way.
This bottom-up approach illuminates unifying themes in the design
of Bayesian optimization algorithms and builds a solid theoretical
foundation for approaching novel situations. The core of the book
is divided into three main parts, covering theoretical and
practical aspects of Gaussian process modeling, the Bayesian
approach to sequential decision making, and the realization and
computation of practical and effective optimization policies.
Following this foundational material, the book provides an overview
of theoretical convergence results, a survey of notable extensions,
a comprehensive history of Bayesian optimization, and an extensive
annotated bibliography of applications.
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