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 ...
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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 (e.g., branch-and-bound), extended formulation, and many aspects of matrix theory. The book is mainly aimed at graduate students and researchers in mathematical optimization and data analytics.
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Add this copy of Maximum-Entropy Sampling: Algorithms and Application to cart. $144.17, new condition, Sold by Ria Christie Books rated 4.0 out of 5 stars, ships from Uxbridge, MIDDLESEX, UNITED KINGDOM, published 2023 by Springer International Publishing AG.
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New. Contains: Illustrations, black & white, Illustrations, color. Springer Series in Operations Research and Financial Engineering . XVII, 195 p. 10 illus., 9 illus. in color. Intended for college/higher education audience.
Add this copy of Maximum-Entropy Sampling: Algorithms and Application to cart. $144.17, new condition, Sold by Ria Christie Books rated 4.0 out of 5 stars, ships from Uxbridge, MIDDLESEX, UNITED KINGDOM, published 2022 by Springer International Publishing AG.
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Seller's Description:
New. Contains: Illustrations, black & white, Illustrations, color. Springer Series in Operations Research and Financial Engineering . XVII, 195 p. 10 illus., 9 illus. in color. Intended for college/higher education audience.
Add this copy of Maximum-Entropy Sampling: Algorithms and Application to cart. $131.11, new condition, Sold by Ingram Customer Returns Center rated 5.0 out of 5 stars, ships from NV, USA, published 2023 by Springer International Publishing AG.
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Seller's Description:
New. Print on demand Contains: Illustrations, black & white, Illustrations, color. Springer Series in Operations Research and Financial Engineering . XVII, 195 p. 10 illus., 9 illus. in color. Intended for college/higher education audience.
Add this copy of Maximum-Entropy Sampling: Algorithms and Application to cart. $131.11, new condition, Sold by Ingram Customer Returns Center rated 5.0 out of 5 stars, ships from NV, USA, published 2022 by Springer International Publishing AG.
Choose your shipping method in Checkout. Costs may vary based on destination.
Seller's Description:
New. Print on demand Contains: Illustrations, black & white, Illustrations, color. Springer Series in Operations Research and Financial Engineering . XVII, 195 p. 10 illus., 9 illus. in color. Intended for college/higher education audience.
