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Yushun Dong
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Edits: Modeling and mitigating data bias for graph neural networks
Y Dong, N Liu, B Jalaian, J Li
Proceedings of the ACM web conference 2022, 1259-1269, 2022
992022
Individual fairness for graph neural networks: A ranking based approach
Y Dong, J Kang, H Tong, J Li
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021
982021
Fairness in graph mining: A survey
Y Dong, J Ma, S Wang, C Chen, J Li
IEEE Transactions on Knowledge and Data Engineering, 2023
782023
Improving fairness in graph neural networks via mitigating sensitive attribute leakage
Y Wang, Y Zhao, Y Dong, H Chen, J Li, T Derr
Proceedings of the 28th ACM SIGKDD conference on knowledge discovery and …, 2022
592022
Adagnn: Graph neural networks with adaptive frequency response filter
Y Dong, K Ding, B Jalaian, S Ji, J Li
Proceedings of the 30th ACM international conference on information …, 2021
482021
Federated graph machine learning: A survey of concepts, techniques, and applications
X Fu, B Zhang, Y Dong, C Chen, J Li
ACM SIGKDD Explorations Newsletter 24 (2), 32-47, 2022
362022
Contrastive attributed network anomaly detection with data augmentation
Z Xu, X Huang, Y Zhao, Y Dong, J Li
Pacific-Asia Conference on Knowledge Discovery and Data Mining, 444-457, 2022
352022
On structural explanation of bias in graph neural networks
Y Dong, S Wang, Y Wang, T Derr, J Li
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022
292022
Guide: Group equality informed individual fairness in graph neural networks
W Song, Y Dong, N Liu, J Li
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022
242022
Assessing the causal impact of COVID-19 related policies on outbreak dynamics: A case study in the US
J Ma, Y Dong, Z Huang, D Mietchen, J Li
Proceedings of the ACM Web Conference 2022, 2678-2686, 2022
222022
Forecasting pavement performance with a feature fusion LSTM-BPNN model
Y Dong, Y Shao, X Li, S Li, L Quan, W Zhang, J Du
Proceedings of the 28th ACM international conference on information and …, 2019
212019
Interpreting unfairness in graph neural networks via training node attribution
Y Dong, S Wang, J Ma, N Liu, J Li
Proceedings of the AAAI Conference on Artificial Intelligence 37 (6), 7441-7449, 2023
192023
Faith: Few-shot graph classification with hierarchical task graphs
S Wang, Y Dong, X Huang, C Chen, J Li
arXiv preprint arXiv:2205.02435, 2022
152022
Empowering next poi recommendation with multi-relational modeling
Z Huang, J Ma, Y Dong, NZ Foutz, J Li
Proceedings of the 45th International ACM SIGIR Conference on Research and …, 2022
142022
Reliant: Fair knowledge distillation for graph neural networks
Y Dong, B Zhang, Y Yuan, N Zou, Q Wang, J Li
Proceedings of the 2023 SIAM International Conference on Data Mining (SDM …, 2023
102023
Few-shot node classification with extremely weak supervision
S Wang, Y Dong, K Ding, C Chen, J Li
Proceedings of the Sixteenth ACM International Conference on Web Search and …, 2023
82023
Gigamae: Generalizable graph masked autoencoder via collaborative latent space reconstruction
Y Shi, Y Dong, Q Tan, J Li, N Liu
Proceedings of the 32nd ACM International Conference on Information and …, 2023
42023
Fairness in Graph Machine Learning: Recent Advances and Future Prospectives
Y Dong, OD Kose, Y Shen, J Li
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023
22023
Empower Post-hoc Graph Explanations with Information Bottleneck: A Pre-training and Fine-tuning Perspective
J Wang, M Luo, J Li, Y Lin, Y Dong, JS Dong, Q Zheng
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023
22023
When Newer is Not Better: Does Deep Learning Really Benefit Recommendation From Implicit Feedback?
Y Dong, J Li, T Schnabel
Proceedings of the 46th International ACM SIGIR Conference on Research and …, 2023
22023
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