Biblio

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Conference Paper
Li, J., H. Zhang, Z. Han, Y. Rong, H. Cheng, and J. Huang, "Adversarial Attack on Community Detection by Hiding Individuals", WWW, pp. 917-927, 2020.
Li, J., J. Yu, J. Li, H. Zhang, K. Zhao, Y. Rong, H. Cheng, and J. Huang, "Dirichlet Graph Variational Autoencoder", NeurIPS, 2020.
Zhao, K., Y. Rong, J. Xu Yu, W. Huang, J. Huang, and H. Zhang, "Graph Ordering: Towards the Optimal by Learning", WISE, pp. 423-437, 2021.
Zhao, K., J. Xu Yu, H. Zhang, Q. Li, and Y. Rong, "A Learned Sketch for Subgraph Counting", SIGMOD, pp. 2142-2155, 2021.
Piao, C., W. Zheng, Y. Rong, and H. Cheng, "Maximizing the Reduction Ability for Near-maximum Independent Set Computation", PVLDB, pp. 2466-2478, 2020.
Rong, Y., and H. Cheng, "Minimizing Dependence between Graphs", Proceedings of the 2017 {ACM} on Conference on Information and Knowledge Management, {CIKM} 2017, Singapore, November 06 - 10, 2017, pp. 1827–1836, 2017.
Rong, Y., Q. Zhu, and H. Cheng, "A Model-Free Approach to Infer the Diffusion Network from Event Cascade", Proceedings of the 25th {ACM} International on Conference on Information and Knowledge Management, {CIKM} 2016, Indianapolis, IN, USA, October 24-28, 2016, pp. 1653–1662, 2016.
Li, J., Y. Rong, H. Cheng, H. Meng, W-. bin Huang, and J. Huang, "Semi-Supervised Graph Classification: A Hierarchical Graph Perspective.", WWW, pp. 972-982, 2019.
Zhao, K., J. Xu Yu, Y. Rong, M. Liao, and J. Huang, "Towards Expectation-Maximization by SQL in RDBMS", DASFAA, pp. 778-794, 2021.
Zhao, K., S. Liu, J. Xu Yu, and Y. Rong, "Towards Feature-free TSP Solver Selection: A Deep Learning Approach", IJCNN, pp. 1-8, 2021.
Rong, Y., H. Cheng, and Z. Mo, "Why It Happened: Identifying and Modeling the Reasons of the Happening of Social Events", Proceedings of the 21th {ACM} {SIGKDD} International Conference on Knowledge Discovery and Data Mining, Sydney, NSW, Australia, August 10-13, 2015, pp. 1015–1024, 2015.
Journal Article
Zhao, K., Z. Zhang, Y. Rong, J. Xu Yu, and J. Huang, "Finding Critical Users in Social Communities via Graph Convolutions", IEEE Trans. Knowl. Data Eng., vol. 35, pp. 456–468, 2023.
Zhao, K., J. Xu Yu, Q. Li, H. Zhang, and Y. Rong, "Learned sketch for subgraph counting: a holistic approach", The VLDB Journal, pp. 1–26, 2023.
Zhao, K., Z. He, J. Xu Yu, and Y. Rong, "Learning with small data: subgraph counting queries", Data Science and Engineering, pp. 1–14, 2023.