Graph convolutional networks of reconstructed graph structure with constrained Laplacian rank

Convolutional neural networks (CNNs) have achieved unprecedented competitiveness in text and two-dimensional image data processing because of its good accuracy performance and high detection speed. Graph convolutional networks (GCNs), as an extension of classical CNNs in graph data processing, have...

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Veröffentlicht in:	Multimedia tools and applications 2022-10, Vol.81 (24), p.34183-34194
Hauptverfasser:	Zhan, Mengmeng, Gan, Jiangzhang, Lu, Guangquan, Wan, Yingying
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Classification Computer Communication Networks Computer Science Constraints Data processing Data Structures and Information Theory Graph theory Graphs Multimedia Information Systems Multivariate analysis Recommender systems Special Purpose and Application-Based Systems
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