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Complexity and Approximation

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Cover of 'Complexity and Approximation'

Table of Contents

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    Book Overview
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    Chapter 1 In Memoriam: Ker-I Ko (1950–2018)
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    Chapter 2 Ker-I Ko and the Study of Resource-Bounded Kolmogorov Complexity
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    Chapter 3 The Power of Self-Reducibility: Selectivity, Information, and Approximation
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    Chapter 4 Who Asked Us? How the Theory of Computing Answers Questions about Analysis
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    Chapter 5 Promise Problems on Probability Distributions
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    Chapter 6 On Nonadaptive Reductions to the Set of Random Strings and Its Dense Subsets
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    Chapter 7 Computability of the Solutions to Navier-Stokes Equations via Effective Approximation
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    Chapter 8 AutoOverview: A Framework for Generating Structured Overviews over Many Documents
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    Chapter 9 Better Upper Bounds for Searching on a Line with Byzantine Robots
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    Chapter 10 A Survey on Double Greedy Algorithms for Maximizing Non-monotone Submodular Functions
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    Chapter 11 Sequential Location Game on Continuous Directional Star Networks
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    Chapter 12 Core Decomposition, Maintenance and Applications
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    Chapter 13 Active and Busy Time Scheduling Problem: A Survey
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    Chapter 14 A Note on the Position Value for Hypergraph Communication Situations
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    Chapter 15 An Efficient Approximation Algorithm for the Steiner Tree Problem
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    Chapter 16 A Review for Submodular Optimization on Machine Scheduling Problems
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    Chapter 17 Edge Computing Integrated with Blockchain Technologies
Attention for Chapter 17: Edge Computing Integrated with Blockchain Technologies
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Chapter title
Edge Computing Integrated with Blockchain Technologies
Chapter number 17
Book title
Complexity and Approximation
Published by
Springer, Cham, January 2020
DOI 10.1007/978-3-030-41672-0_17
Book ISBNs
978-3-03-041671-3, 978-3-03-041672-0
Authors

Chuanwen Luo, Liya Xu, Deying Li, Weili Wu, Luo, Chuanwen, Xu, Liya, Li, Deying, Wu, Weili

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 52 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 21%
Student > Master 9 17%
Student > Postgraduate 3 6%
Student > Doctoral Student 2 4%
Lecturer 2 4%
Other 7 13%
Unknown 18 35%
Readers by discipline Count As %
Computer Science 25 48%
Engineering 6 12%
Social Sciences 1 2%
Biochemistry, Genetics and Molecular Biology 1 2%
Unknown 19 37%