{"product_id":"bayesian-optimization-9781108425780","title":"Bayesian Optimization","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003eBayesian optimization is a successful methodology for optimizing expensive objective functions across various fields. This book offers a comprehensive introduction, covering theoretical and practical aspects, with a focus on Gaussian process modeling, sequential decision-making, and practical optimization policies. It provides theoretical convergence results, surveys notable extensions, offers a history of Bayesian optimization, and includes an annotated bibliography of applications. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Hardback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 358 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 09 February 2023\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Cambridge University Press\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eBayesian optimization is a powerful methodology for optimizing complex objective functions across a wide range of fields, including science, engineering, and beyond. This comprehensive and timely text offers a thorough introduction to the subject, starting from the basics and gradually building upon key concepts. By taking a bottom-up approach, the book uncovers common themes in the design of Bayesian optimization algorithms and establishes a solid theoretical foundation for tackling new challenges.\u003cbr\u003e\u003cbr\u003eThe core of the book is organized into three main parts. The first part focuses on theoretical aspects of Gaussian process modeling, providing a comprehensive understanding of the underlying principles and techniques. The second part explores the Bayesian approach to sequential decision-making, highlighting its advantages and applications in various domains. The third part delves into the practical implementation and computation of optimization policies, showcasing real-world examples and strategies.\u003cbr\u003e\u003cbr\u003eIn addition to its theoretical foundation, the book provides an overview of theoretical convergence results, surveys notable extensions and applications, offers a comprehensive history of Bayesian optimization, and includes an extensive annotated bibliography of relevant applications. Whether you are a researcher, practitioner, or student interested in optimization, this book serves as a valuable resource for gaining a deeper understanding of Bayesian optimization and its applications in modern science and technology.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 1028g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 259 x 211 x 24 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9781108425780\u003c\/p\u003e","brand":"RomanGarnett","offers":[{"title":"Hardback","offer_id":44094852301050,"sku":"9781108425780","price":47.82,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/1676036584294_book.jpg?v=1676564979","url":"https:\/\/shulphink.com\/products\/bayesian-optimization-9781108425780","provider":"Shulph Ink","version":"1.0","type":"link"}