Dynamics On and Of Complex Networks III: Machine Learning and Statistical Physics Approaches

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Book: Dynamics On and Of Complex Networks III: Machine Learning and Statistical Physics Approaches
Author(s): Fakhteh Ghanbarnejad, Rishiraj Saha Roy, Fariba Karimi, Jean-Charles Delvenne and Bivas Mitra
Publisher: Springer
Tags: Network Dynamics, Machine Learning, Complex Systems.
Year: 1st Edition (May 25, 2019)
Print Length: 246 pages
Format: EPUB, PDF (True)
Language: English
ISBN-10: 3030146820
ISBN-13: 9783030146825
Size: 30.3 MB (Rar)

Synopsis
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, together with new invited contributions. The chapters will benefit a diverse community of researchers.

Who This Book Is For
The book is suitable for graduate students, postdoctoral researchers and professors of various disciplines including sociology, physics, mathematics, and computer science.

Table Of Contents:
Part I. Network Structure
    An Empirical Study of the Effect of Noise Models on Centrality Metrics
    Emergence and Evolution of Hierarchical Structure in Complex Systems
    Evaluation of Cascading Infrastructure Failures and Optimal Recovery from a Network Science Perspective
Part II. Network Dynamics
    Automatic Discovery of Families of Network Generative Processes
    Modeling User Dynamics in Collaboration Websites
    Interaction Prediction Problems in Link Streams
    The Network Source Location Problem in the Context of Foodborne Disease Outbreaks
Part III. Theoretical Models and Applications
    Network Representation Learning Using Local Sharing and Distributed Matrix Factorization (LSDMF)
    The Anatomy of Reddit: An Overview of Academic Research
    Learning Information Dynamics in Online Social Media: A Temporal Point Process Perspective

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Edited February 18, 2020 by Bad Karma
Dead links removed