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08/15/2023
Simple and Efficient Partial Graph Adversarial Attack: A New Perspective
As the study of graph neural networks becomes more intensive and compreh...
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07/04/2023
HAGNN: Hybrid Aggregation for Heterogeneous Graph Neural Networks
Heterogeneous graph neural networks (GNNs) have been successful in handl...
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01/08/2023
AutoAC: Towards Automated Attribute Completion for Heterogeneous Graph Neural Network
Many real-world data can be modeled as heterogeneous graphs that contain...
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10/07/2022
A2: Efficient Automated Attacker for Boosting Adversarial Training
Based on the significant improvement of model robustness by AT (Adversar...
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07/21/2022
Knowledge-enhanced Black-box Attacks for Recommendations
Recent studies have shown that deep neural networks-based recommender sy...
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03/12/2022
Transition Relation Aware Self-Attention for Session-based Recommendation
Session-based recommendation is a challenging problem in the real-world ...
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08/04/2021
UniGPS: A Unified Programming Framework for Distributed Graph Processing
The industry and academia have proposed many distributed graph processin...
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10/17/2020
DIFER: Differentiable Automated Feature Engineering
Feature engineering, a crucial step of machine learning, aims to extract...
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05/29/2020