Online Graph-Adaptive Learning With Scalability and Privacy

Graphs are widely adopted for modeling complex systems, including financial, biological, and social networks. Nodes in networks usually entail attributes, such as the age or gender of users in a social network. However, real-world networks can have very large size, and nodal attributes can be unavai...

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Veröffentlicht in:	IEEE transactions on signal processing Jg. 67; H. 9; S. 2471 - 2483
Hauptverfasser:	Shen, Yanning, Leus, Geert, Giannakis, Georgios B.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.05.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Adaptive learning Companies Complex systems Distance learning Estimation Graph signal reconstruction Kernel kernel-based learning learning over dynamic graphs Nodes online learning Privacy Real time Real-time systems Social networking (online) Social networks Task analysis
ISSN:	1053-587X, 1941-0476
Online-Zugang:	Volltext
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