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Prediction of Rolling Force Based on a Fusion of Extreme Learning Machine and Self Learning Model of Rolling Force Read chapter Read first chapter

2018 | OriginalPaper | Chapter

The Greedy Algorithm and Its Performance Guarantees for Solving Maximization of Submodular Function

Authors : Yunxia Guo, Guohong Liang, Jia Liu

Published in: Advances in Intelligent Systems and Interactive Applications

Publisher: Springer International Publishing

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Abstract

Maximizing or minimizing submodular function is widely used in combinatorial optimization problems. In this paper; we present an approximation algorithm for maximizing submodular function subject to independence system that be represented as the intersection of a limited number of matroids, and discuss its performance guarantee.

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Literature
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Gao, Y., Hao, Z., He, S.: An approximate algorithm for solving the maximum value of the function of non-increasing modulus function and its performance guarantee. Pract. Underst. Mathe. 12(38), 148–149 (2008)
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Narayanan, H.: Submodular functions and electrical networks. Vehicles: North Holland (1997)
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Wang, W., Zhang, F., TuoXiaoli, He, S.: Local search algorithm for solving maximizing submodular set function. J. Wenzhou University (3) 2008
Metadata
Title
The Greedy Algorithm and Its Performance Guarantees for Solving Maximization of Submodular Function
Authors
Yunxia Guo
Guohong Liang
Jia Liu
Copyright Year
2018
Book
Advances in Intelligent Systems and Interactive Applications

Print ISBN: 978-3-319-69095-7

Electronic ISBN: 978-3-319-69096-4

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-69096-4_108

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