Dynamics On and Of Complex Networks III
Machine Learning and Statistical Physics Approaches
Editors: Ghanbarnejad, F., Saha Roy, R., Karimi, F., Delvenne, J.-C., Mitra, B. (Eds.)
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- About this book
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This book bridges the gap between advances in the communities of computer science and physics--namely machine learning and statistical physics. It contains diverse but relevant topics in statistical physics, complex systems, network theory, and machine learning. Examples of such topics are: predicting missing links, higher-order generative modeling of networks, inferring network structure by tracking the evolution and dynamics of digital traces, recommender systems, and diffusion processes.
The book contains extended versions of high-quality submissions received at the workshop, Dynamics On and Of Complex Networks (doocn.org), together with new invited contributions. The chapters will benefit a diverse community of researchers. The book is suitable for graduate students, postdoctoral researchers and professors of various disciplines including sociology, physics, mathematics, and computer science.
- Table of contents (10 chapters)
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An Empirical Study of the Effect of Noise Models on Centrality Metrics
Pages 3-21
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Emergence and Evolution of Hierarchical Structure in Complex Systems
Pages 23-62
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Evaluation of Cascading Infrastructure Failures and Optimal Recovery from a Network Science Perspective
Pages 63-79
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Automatic Discovery of Families of Network Generative Processes
Pages 83-111
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Modeling User Dynamics in Collaboration Websites
Pages 113-133
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Table of contents (10 chapters)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Dynamics On and Of Complex Networks III
- Book Subtitle
- Machine Learning and Statistical Physics Approaches
- Editors
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- Fakhteh Ghanbarnejad
- Rishiraj Saha Roy
- Fariba Karimi
- Jean-Charles Delvenne
- Bivas Mitra
- Series Title
- Springer Proceedings in Complexity
- Copyright
- 2019
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer Nature Switzerland AG
- eBook ISBN
- 978-3-030-14683-2
- DOI
- 10.1007/978-3-030-14683-2
- Hardcover ISBN
- 978-3-030-14682-5
- Softcover ISBN
- 978-3-030-14685-6
- Series ISSN
- 2213-8684
- Edition Number
- 1
- Number of Pages
- X, 244
- Number of Illustrations
- 8 b/w illustrations, 68 illustrations in colour
- Topics
