| 書目名稱 | Maximum-Entropy Sampling | | 副標(biāo)題 | Algorithms and Appli | | 編輯 | Marcia Fampa,Jon Lee | | 視頻video | http://file.papertrans.cn/628/627919/627919.mp4 | | 概述 | Aimed at graduate students and researchers in optimization and data analytics.Concerns the MESP at the intersection of optimization algorithms and data science.There is no other book on this subject | | 叢書名稱 | Springer Series in Operations Research and Financial Engineering | | 圖書封面 |  | | 描述 | This monograph presents a comprehensive treatment of the maximum-entropy sampling problem (MESP), which is a fascinating topic at the intersection of mathematical optimization?and data science. The text situates MESP in information theory, as the algorithmic problem of calculating a sub-vector of pre-specificed?size from a multivariate Gaussian random vector, so as to maximize Shannon‘s differential entropy. The text collects and expands on state-of-the-art algorithms for MESP, and addresses its application in the field of environmental monitoring. While MESP is a central optimization problem in the theory of statistical designs (particularly in the area of spatial monitoring), this book largely focuses on the unique challenges of its algorithmic side. From the perspective of mathematical-optimization methodology, MESP is rather unique (a 0/1 nonlinear program having a nonseparable objective function), and the algorithmic techniques employed are highly non-standard. In particular, successful techniques come from several disparate areas within the field of mathematical optimization; for example: convex optimization and duality, semidefinite programming, Lagrangian relaxation, dynami | | 出版日期 | Book 2022 | | 關(guān)鍵詞 | maximum-entropy sampling; integer nonlinear programming; global optimization; differential entropy; envi | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-13078-6 | | isbn_softcover | 978-3-031-13080-9 | | isbn_ebook | 978-3-031-13078-6Series ISSN 1431-8598 Series E-ISSN 2197-1773 | | issn_series | 1431-8598 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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