| Inform: Individual fairness on graph mining J Kang, J He, R Maciejewski, H Tong Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 108 | 2020 |
| 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 | 98 | 2021 |
| RawlsGCN: Towards Rawlsian Difference Principle on Graph Convolutional Network J Kang, Y Zhu, Y Xia, J Luo, H Tong Proceedings of the ACM Web Conference 2022, 2022 | 44 | 2022 |
| Do we really need complicated model architectures for temporal networks? W Cong, S Zhang, J Kang, B Yuan, H Wu, X Zhou, H Tong, M Mahdavi arXiv preprint arXiv:2302.11636, 2023 | 39 | 2023 |
| Infofair: Information-theoretic intersectional fairness J Kang, T Xie, X Wu, R Maciejewski, H Tong 2022 IEEE International Conference on Big Data (Big Data), 1455-1464, 2022 | 33* | 2022 |
| Fair graph mining J Kang, H Tong Proceedings of the 30th ACM International Conference on Information …, 2021 | 29 | 2021 |
| Fairrankvis: A visual analytics framework for exploring algorithmic fairness in graph mining models T Xie, Y Ma, J Kang, H Tong, R Maciejewski IEEE Transactions on Visualization and Computer Graphics 28 (1), 368-377, 2021 | 25 | 2021 |
| N2n: Network derivative mining J Kang, H Tong Proceedings of the 28th ACM International Conference on Information and …, 2019 | 18 | 2019 |
| JuryGCN: quantifying jackknife uncertainty on graph convolutional networks J Kang, Q Zhou, H Tong Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 17 | 2022 |
| Aurora: Auditing pagerank on large graphs J Kang, M Wang, N Cao, Y Xia, W Fan, H Tong 2018 IEEE International Conference on Big Data (Big Data), 713-722, 2018 | 17 | 2018 |
| X-rank: Explainable ranking in complex multi-layered networks J Kang, S Freitas, H Yu, Y Xia, N Cao, H Tong Proceedings of the 27th ACM International Conference on Information and …, 2018 | 11 | 2018 |
| Graph Ranking Auditing: Problem Definition and Fast Solutions M Wang, J Kang, N Cao, Y Xia, W Fan, H Tong IEEE Transactions on Knowledge and Data Engineering, 2020 | 9 | 2020 |
| IMBENS: Ensemble class-imbalanced learning in Python Z Liu, J Kang, H Tong, Y Chang arXiv preprint arXiv:2111.12776, 2021 | 7 | 2021 |
| Algorithmic fairness on graphs: Methods and trends J Kang, H Tong Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 6 | 2022 |
| Bemap: Balanced message passing for fair graph neural network X Lin, J Kang, W Cong, H Tong arXiv preprint arXiv:2306.04107, 2023 | 5 | 2023 |
| ifig: Individually fair multi-view graph clustering Y Wang, J Kang, Y Xia, J Luo, H Tong 2022 IEEE International Conference on Big Data (Big Data), 329-338, 2022 | 4 | 2022 |
| Ensuring User-side Fairness in Dynamic Recommender Systems H Yoo, Z Zeng, J Kang, Z Liu, D Zhou, F Wang, E Chan, H Tong arXiv preprint arXiv:2308.15651, 2023 | 1 | 2023 |
| Theoretical and Empirical Insights into the Origins of Degree Bias in Graph Neural Networks A Subramonian, J Kang, Y Sun arXiv preprint arXiv:2404.03139, 2024 | | 2024 |
| On the Generalization Capability of Temporal Graph Learning Algorithms: Theoretical Insights and a Simpler Method W Cong, J Kang, H Tong, M Mahdavi arXiv preprint arXiv:2402.16387, 2024 | | 2024 |
| Deceptive Fairness Attacks on Graphs via Meta Learning J Kang, Y Xia, R Maciejewski, J Luo, H Tong arXiv preprint arXiv:2310.15653, 2023 | | 2023 |
Hanghang TongUniversity of Illinois at Urbana-ChampaignVerified email at illinois.edu
