Titlebook: Machine Learning in Complex Networks; Thiago Christiano Silva,Liang Zhao Book 2016 Springer International Publishing Switzerland 2016 Comm

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Case Study of Network-Based Unsupervised Learning: Stochastic Competitive Learning in Networks,sses interesting properties, runs roughly in linear time for sparse networks, and also has good performance on artificial and real-world networks. In the initial setup, a set of particles is released into vertices of a network in a random manner.As time progresses, they move across the network in ac

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Case Study of Network-Based Semi-Supervised Learning: Stochastic Competitive-Cooperative Learning iifically, this enhancement is achieved by introducing the idea of cooperationamong the particles and by changing the inner mechanisms of the original algorithm so as to fit it into a semi-supervised environment. In contrast to the unsupervised learning model, where the particles are randomly spawned

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https://doi.org/10.1007/978-3-319-17290-3Community Detection; Complex Networks; Data Classification; Data Clustering; Machine Learning

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Introduction,the word “complexity.” What happens when we put together these two concepts? In this chapter, we present an overview on complex network-based machine learning. Throughout the entire book, we show the diversity of approaches for treating such a subject.

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Thiago Christiano Silva,Liang ZhaoThis book combines two important and popular research areas: complex networks and machine learning.This book contains not only fundamental background, but also recent research results.Numerous illustr

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