Название: Bayesian Optimization and Data Science (SpringerBriefs in Optimization)
Автор: Francesco Archetti, Antonio Candelieri
Издательство: Springer
Год: 2019
Формат: True PDF/ePub
Страниц: 126
Размер: 16.2 Mb
Язык: English

This volume brings together the main results in the field of Bayesian Optimization (BO), focusing on the last ten years and showing how, on the basic framework, new methods have been specialized to solve emerging problems from machine learning, artificial intelligence, and system optimization. It also analyzes the software resources available for BO and a few selected application areas. Some areas for which new results are shown include constrained optimization, safe optimization, and applied mathematics, specifically BO's use in solving difficult nonlinear mixed integer problems.