http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
xvi, 358 pages : illustrations (some color) ; 26 cm.
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.
Roman Garnett, Washington University in St. Louis.
Includes bibliographical references (pages 331-351) and index.