| Revisiting the stop-and-stare algorithms for influence maximization K Huang, S Wang, G Bevilacqua, X Xiao, LVS Lakshmanan Proceedings of the VLDB Endowment 10 (9), 913-924, 2017 | 71 | 2017 |
| Efficient algorithms for adaptive influence maximization K Han, K Huang, X Xiao, J Tang, A Sun, X Tang Proceedings of the VLDB Endowment 11 (9), 1029-1040, 2018 | 28 | 2018 |
| Efficient approximation algorithms for adaptive seed minimization J Tang, K Huang, X Xiao, LVS Lakshmanan, X Tang, A Sun, A Lim Proceedings of the 2019 International Conference on Management of Data, 1096 …, 2019 | 11 | 2019 |
| Refutations on" Debunking the Myths of Influence Maximization: An In-Depth Benchmarking Study" W Lu, X Xiao, A Goyal, K Huang, LVS Lakshmanan arXiv preprint arXiv:1705.05144, 2017 | 5 | 2017 |
| Efficient approximation algorithms for adaptive target profit maximization K Huang, J Tang, X Xiao, A Sun, A Lim 2020 IEEE 36th International Conference on Data Engineering (ICDE), 649-660, 2020 | 3 | 2020 |
| Efficient approximation algorithms for adaptive influence maximization K Huang, J Tang, K Han, X Xiao, W Chen, A Sun, X Tang, A Lim The VLDB Journal, 1-22, 2020 | 2 | 2020 |
| Effective and Scalable Clustering on Massive Attributed Graphs R Yang, J Shi, Y Yang, K Huang, S Zhang, X Xiao arXiv preprint arXiv:2102.03826, 2021 | | 2021 |
| Best Bang for the Buck: Cost-Effective Seed Selection for Online Social Networks K Han, Y He, K Huang, X Xiao, S Tang, J Xu, L Huang IEEE Transactions on Knowledge and Data Engineering 32 (12), 2297-2309, 2019 | | 2019 |
| EFFICIENT ADAPTIVE APPROXIMATION ALGORITHMS IN ONLINE SOCIAL NETWORKS H Keke Nanyang Technological University, 2019 | | 2019 |
Xiaokui XiaoNational University of SingaporeVerified email at nus.edu.sg
