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

Brossura

ISBN 10: 3030146855 ISBN 13: 9783030146856

Casa editrice: Springer, 2020

Riassunto

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.

Su questo libro

Dalla quarta di copertina

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.

Dettagli dell'edizione

• Editore: Springer
• Data di pubblicazione: 2020
• Lingua: Inglese
• ISBN 10: 3030146855
• ISBN 13: 9783030146856
• Rilegatura: Copertina flessibile
• Numero edizione: 1
• Numero di pagine: 256
• Redattore: Ghanbarnejad Fakhteh, Saha Roy Rishiraj, Karimi Fariba, Delvenne Jean-Charles, Mitra Bivas
• Contatto del produttore: non disponibile
• Persona responsabile: CMN Printpool Inh. Mathis Neumann; https://www.also.com/ec/cms5/en_6000/6000/index.jsp; ; Friedrich-Karl-Str. 9; Hamburg; Germania