| Mitigating gender bias for neural dialogue generation with adversarial learning H Liu, W Wang, Y Wang, H Liu, Z Liu, J Tang arXiv preprint arXiv:2009.13028, 2020 | 61 | 2020 |
| FLAP: An end-to-end event log analysis platform for system management T Li, Y Jiang, C Zeng, B Xia, Z Liu, W Zhou, X Zhu, W Wang, L Zhang, ... Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge …, 2017 | 51 | 2017 |
| Mining top-k distinguishing sequential patterns with gap constraint H Yang, L Duan, B Hu, S Deng, W Wang, P Qin J. Softw 26 (11), 2994-3009, 2015 | 26 | 2015 |
| Global-and-local aware data generation for the class imbalance problem W Wang, S Wang, W Fan, Z Liu, J Tang Proceedings of the 2020 SIAM International Conference on Data Mining, 307-315, 2020 | 22 | 2020 |
| Online inference for time-varying temporal dependency discovery from time series C Zeng, Q Wang, W Wang, T Li, L Shwartz 2016 IEEE International Conference on Big Data (Big Data), 1281-1290, 2016 | 21 | 2016 |
| Imbalanced adversarial training with reweighting W Wang, H Xu, X Liu, Y Li, B Thuraisingham, J Tang 2022 IEEE International Conference on Data Mining (ICDM), 1209-1214, 2022 | 18 | 2022 |
| Toward degree bias in embedding-based knowledge graph completion H Shomer, W Jin, W Wang, J Tang Proceedings of the ACM Web Conference 2023, 705-715, 2023 | 16 | 2023 |
| DI-DAP: an efficient disaster information delivery and analysis platform in disaster management T Li, W Zhou, C Zeng, Q Wang, Q Zhou, D Wang, J Xu, Y Huang, W Wang, ... Proceedings of the 25th ACM international on conference on information and …, 2016 | 14 | 2016 |
| Representation learning from limited educational data with crowdsourced labels W Wang, G Xu, W Ding, GY Huang, G Li, J Tang, Z Liu IEEE Transactions on Knowledge and Data Engineering 34 (6), 2886-2898, 2020 | 13 | 2020 |
| Oases: an online scalable spam detection system for social networks H Xu, L Hu, P Liu, Y Xiao, W Wang, J Dayal, Q Wang, Y Tang 2018 IEEE 11th International Conference on Cloud Computing (CLOUD), 98-105, 2018 | 11 | 2018 |
| FIU-Miner (a fast, integrated, and user-friendly system for data mining) and its applications T Li, C Zeng, W Zhou, W Xue, Y Huang, Z Liu, Q Zhou, B Xia, Q Wang, ... Knowledge and Information Systems 52, 411-443, 2017 | 11 | 2017 |
| INS-GNN: Improving graph imbalance learning with self-supervision X Juan, F Zhou, W Wang, W Jin, J Tang, X Wang Information Sciences 637, 118935, 2023 | 9 | 2023 |
| Towards the memorization effect of neural networks in adversarial training H Xu, X Liu, W Wang, W Ding, Z Wu, Z Liu, A Jain, J Tang arXiv preprint arXiv:2106.04794, 2021 | 5 | 2021 |
| Learning from incomplete labeled data via adversarial data generation W Wang, T Derr, Y Ma, S Wang, H Liu, Z Liu, J Tang 2020 IEEE International Conference on Data Mining (ICDM), 1316-1321, 2020 | 5 | 2020 |
| Mining frequent closed sequential patterns with non-user-defined gap constraints W Wang, L Duan, J Nummenmaa, S Deng, Z Li, H Yang, C Tang International Conference on Advanced Data Mining and Applications, 57-70, 2014 | 5 | 2014 |
| Discovering multiple time lags of temporal dependencies from fluctuating events W Wang, C Zeng, T Li Web and Big Data: Second International Joint Conference, APWeb-WAIM 2018 …, 2018 | 3 | 2018 |
| A Mix-up Strategy to Enhance Adversarial Training with Imbalanced Data W Wang, H Shomer, Y Wan, Y Li, J Huang, H Liu Proceedings of the 32nd ACM International Conference on Information and …, 2023 | 1 | 2023 |
| Towards adversarial learning: from evasion attacks to poisoning attacks W Wang, H Xu, Y Wan, J Ren, J Tang Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 1 | 2022 |
| Enhancing Adversarial Training with Feature Separability Y Li, X Liu, H Xu, W Wang, J Tang arXiv preprint arXiv:2205.00637, 2022 | 1 | 2022 |
| Learning from Imbalanced Crowdsourced Labeled Data W Wang, J Thekinen, X Liu, Z Liu, J Tang Proceedings of the 2022 SIAM International Conference on Data Mining (SDM …, 2022 | 1 | 2022 |
