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A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources
Heterogeneous graphs (HGs) also known as heterogeneous information netwo...
11/30/2020 ∙ by Xiao Wang, et al. ∙
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Interpretable Deep Graph Generation with Node-Edge Co-Disentanglement
Disentangled representation learning has recently attracted a significan...
06/09/2020 ∙ by Xiaojie Guo, et al. ∙
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SoK: Arms Race in Adversarial Malware Detection
Malicious software (malware) is a major cyber threat that shall be tackl...
05/24/2020 ∙ by Deqiang Li, et al. ∙
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Enhancing Deep Neural Networks Against Adversarial Malware Examples
Machine learning based malware detection is known to be vulnerable to ad...
04/15/2020 ∙ by Deqiang Li, et al. ∙
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α-Satellite: An AI-driven System and Benchmark Datasets for Hierarchical Community-level Risk Assessment to Help Combat COVID-19
The novel coronavirus and its deadly outbreak have posed grand challenge...
03/27/2020 ∙ by Yanfang Ye, et al. ∙
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Hyperbolic Graph Attention Network
Graph neural network (GNN) has shown superior performance in dealing wit...
12/06/2019 ∙ by Yiding Zhang, et al. ∙
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Temporal Network Embedding with Micro- and Macro-dynamics
Network embedding aims to embed nodes into a low-dimensional space, whil...
09/10/2019 ∙ by Yuanfu Lu, et al. ∙
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Enhancing Robustness of Deep Neural Networks Against Adversarial Malware Samples: Principles, Framework, and AICS'2019 Challenge
Malware continues to be a major cyber threat, despite the tremendous eff...
12/19/2018 ∙ by Deqiang Li, et al. ∙
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AiDroid: When Heterogeneous Information Network Marries Deep Neural Network for Real-time Android Malware Detection
The explosive growth and increasing sophistication of Android malware ca...
11/02/2018 ∙ by Yanfang Ye, et al. ∙
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