Similarity-Aware Network Embedding with Self-Paced Learning
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, pp. 2113-2116, 2019.
deep neural network network embedding self-paced learning
Network embedding, which aims to learn low-dimensional vector representations for nodes in a network, has shown promising performance for many real-world applications, such as node classification and clustering. While various embedding methods have been developed for network data, they are limited in their assumption that nodes are correl...More
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