Bayesian Optimization and Data Science
Author | : Francesco Archetti |
Publisher | : Springer |
Total Pages | : 126 |
Release | : 2019-10-07 |
ISBN-10 | : 3030244938 |
ISBN-13 | : 9783030244934 |
Rating | : 4/5 (934 Downloads) |
Download or read book Bayesian Optimization and Data Science written by Francesco Archetti and published by Springer. This book was released on 2019-10-07 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. The book will help bring readers to a full understanding of the basic Bayesian Optimization framework and gain an appreciation of its potential for emerging application areas. It will be of particular interest to the data science, computer science, optimization, and engineering communities.