This book explores the features and advantages offered by complex networks in the domain of machine learning. In the first part of the book, we present an overview on complex networks and machine learning. Then, we provide a comprehensive description on network-based machine lea…
This book explores the features and advantages offered by complex networks in the domain of machine learning. In the first part of the book, we present an overview on complex networks and machine learning. Then, we provide a comprehensive description on network-based machine lea…
Les sciences non linéaires ont pour objet l'ensemble des phénomènes dont l'analyse résiste au principe de superposition. Elles concernent en grande partie les systèmes dits {laquo} complexes {raquo} dont l'interaction et l'interdépendance entre les parties empêchent de prédire p…
by Kalton, Michael C., Mobus, George E.
fromUnderstanding complex systems
by Thai, My T.
fromHandbook of optimization in complex networks / My T.
This book develops a mathematical framework for modeling and optimizing interference-coupled multiuser systems. At the core of this framework is the concept of general interference functions, which provides a simple means of characterizing interdependencies between users. The en…
Complex systems are systems that comprise many interacting parts with the ability to generate a new quality of collective behavior through self-organization, e.g. the spontaneous formation of temporal, spatial or functional structures. These systems are often characterized by ex…
Today it appears that we understand more about the universe than about our interconnected socio-economic world. In order to uncover organizational structures and novel features in these systems, we present the first comprehensive complex systems analysis of real-world ownership …
A graph consists of vertices and edges, connecting pairs of vertices. The subject of graph generation has a long history. Initial research focused on creating catalogues of graphs of small size. It has proved useful for creating input instances for different graph algorithms as …
Identifying influential individuals is a well-known approach in extracting actionable knowledge in a network. Previous researches suggest measures to identify influential individuals, e.g., they focus on the question "which individuals are best connected to others or have the mo…
