Bayesian Optimization With Application To Computer Experiments

Description: Please refer to the section BELOW (and NOT ABOVE) this line for the product details - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Title:Bayesian Optimization With Application To Computer ExperimentsISBN13:9783030824570ISBN10:3030824578Author:Pourmohamad, Tony (Author), Lee, Herbert (Author)Description:This Book Introduces Readers To Bayesian Optimization, Highlighting Advances In The Field And Showcasing Its Successful Applications To Computer Experiments R Code Is Available As Online Supplementary Material For Most Included Examples, So That Readers Can Better Comprehend And Reproduce Methods Compact And Accessible, The Volume Is Broken Down Into Four Chapters Chapter 1 Introduces The Reader To The Topic Of Computer Experiments; It Includes A Variety Of Examples Across Many Industries Chapter 2 Focuses On The Task Of Surrogate Model Building And Contains A Mix Of Several Different Surrogate Models That Are Used In The Computer Modeling And Machine Learning Communities Chapter 3 Introduces The Core Concepts Of Bayesian Optimization And Discusses Unconstrained Optimization Chapter 4 Moves On To Constrained Optimization, And Showcases Some Of The Most Novel Methods Found In The Field This Will Be A Useful Companion To Researchers And Practitioners Working With Computer Experiments And Computer Modeling Additionally, Readers With A Background In Machine Learning But Minimal Background In Computer Experiments Will Find This Book An Interesting Case Study Of The Applicability Of Bayesian Optimization Outside The Realm Of Machine Learning Binding:Paperback, PaperbackPublisher:SpringerPublication Date:2021-10-25Weight:0 lbsDimensions:Number of Pages:90Language:English

Price: 73.51 USD

Location: USA

End Time: 2024-11-22T01:57:48.000Z

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