Deep Self-Supervised Graph Attention Convolution Autoencoder for Networks Clustering

In recent years, graph-based deep learning algorithms have attracted widespread attention in the field of consumer electronics. Still, most of the current graph neural networks are based on supervised learning or semi-supervised learning, which often relies on the true labels of the given samples as...

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Veröffentlicht in:	IEEE transactions on consumer electronics 2023-11, Vol.69 (4), p.974-983
Hauptverfasser:	Chen, Chao, Lu, Hu, Hong, Haotian, Wang, Hai, Wan, Shaohua
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms autoencoder Clustering Clustering algorithms Convolution Deep learning Feature extraction Graph neural networks Labels Machine learning Neural networks Reliability reliable sample selection Self-supervised Self-supervised learning Semi-supervised learning Social networking (online) Social networks social networks clustering Source code Unsupervised learning
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