graph embedding

Familial Clustering For Weakly-labeled Android Malware Using Hybrid Representation Learning
Labeling malware or malware clustering is important for identifying new security threats, triaging and building reference datasets. The …
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Adaptive knowledge subgraph ensemble for robust and trustworthy knowledge graph completion
Knowledge graph (KG) embedding approaches are widely used to infer underlying missing facts based on intrinsic structure information. …
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Learning Graph Embedding With Adversarial Training Methods
Graph embedding aims to transfer a graph into vectors to facilitate subsequent graph-analytics tasks like link prediction and graph …
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