书目名称 | High-Dimensional Optimization |
副标题 | Set Exploration in t |
编辑 | Jack Noonan,Anatoly Zhigljavsky |
视频video | |
概述 | A thorough discussion on the properties and geometrical features of high-dimensional sets.Results on the rate of convergence of a wide class of stochastic global optimization algorithms.Detailed study |
丛书名称 | SpringerBriefs in Optimization |
图书封面 |  |
描述 | .This book is interdisciplinary and unites several areas of applied probability, statistics, and computational mathematics including computer experiments, optimal experimental design, and global optimization. The bulk of the book is based on several recent papers by the authors but also contains new results. Considering applications, this brief highlights multistart and other methods of global optimizations requiring efficient exploration of the domain of optimization. This book is accessible to a wide range of readers; the prerequisites for reading the book are rather low, and many numerical examples are provided that pictorially illustrate the main ideas, methods, and conclusions...The main purpose of this book is the construction of efficient exploration strategies of high-dimensional sets. In high dimensions, the asymptotic arguments could be practically misleading and hence the emphasis on the non-asymptotic regime. An important link with global optimization stems from the observation that approximate covering is one of the key concepts associated with multistart and other key random search algorithms. In addition to global optimization, important applications of the results a |
出版日期 | Book 2024 |
关键词 | quantization; statistical inference; non-asymptotic; Lq norms; high-dimensional cubes; efficient quantiza |
版次 | 1 |
doi | https://doi.org/10.1007/978-3-031-58909-6 |
isbn_softcover | 978-3-031-58908-9 |
isbn_ebook | 978-3-031-58909-6Series ISSN 2190-8354 Series E-ISSN 2191-575X |
issn_series | 2190-8354 |
copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |