Description: Maximum-entropy Sampling : Algorithms and Application, Paperback by Fampa, Marcia; Lee, Jon, ISBN 3031130804, ISBN-13 9783031130809, Brand New, Free shipping in the US 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, dynamic programming, approximation algorithms, 0/1 optimization (., branch-and-bound), extended formulation, and many aspects of matrix theory. Th is mainly aimed at graduate students and researchers in mathematical optimization and data analytics.
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Book Title: Maximum-entropy Sampling : Algorithms and Application
Number of Pages: Xvii, 195 Pages
Language: English
Publication Name: Maximum-Entropy Sampling : Algorithms and Application
Publisher: Springer International Publishing A&G
Subject: Operations Research, General, Management Science, Optimization
Publication Year: 2023
Item Weight: 11.9 Oz
Type: Textbook
Subject Area: Mathematics, Science, Business & Economics
Item Length: 9.3 in
Author: Jon Lee, Marcia Fampa
Series: Springer Series in Operations Research and Financial Engineering Ser.
Item Width: 6.1 in
Format: Trade Paperback
