This book presents the features and advantages offered by complex networks in the machine learning domain. In the first part, an overview on complex networks an

This book bridges the gap between advances in the communities of computer science and physics--namely machine learning and statistical physics. It contains dive

This book deals with network representation learning. It deals with embedding nodes, edges, subgraphs and graphs. There is a growing interest in understanding c

Filling a gap in literature, this self-contained book presents theoretical and application-oriented results that allow for a structural exploration of complex n

This book provides a comprehensive yet short description of the basic concepts of Complex Network theory. In contrast to other books the authors present these c