Dynamics On and Of Complex Networks III - Machine Learning and Statistical Physics Approaches (Hardcover, 1st ed. 2019)

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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Springer Proceedings in Complexity
Release date:	May 2019
First published:	2019
Editors:	Fakhteh Ghanbarnejad • Rishiraj Saha Roy • Fariba Karimi • Jean-Charles Delvenne • Bivas Mitra
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	244
Edition:	1st ed. 2019
ISBN-13:	978-3-03-014682-5
Categories:	Books > Reference & Interdisciplinary > Communication studies > Information theory > Cybernetics & systems theory Promotions
LSN:	3-03-014682-0
Barcode:	9783030146825

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