| The emerging trends of multi-label learning W Liu, H Wang, X Shen, IW Tsang IEEE transactions on pattern analysis and machine intelligence 44 (11), 7955 …, 2021 | 350 | 2021 |
| Better diffusion models further improve adversarial training Z Wang, T Pang, C Du, M Lin, W Liu, S Yan International Conference on Machine Learning, 36246-36263, 2023 | 238 | 2023 |
| Metric learning for multi-output tasks W Liu, D Xu, IW Tsang, W Zhang IEEE transactions on pattern analysis and machine intelligence 41 (2), 408-422, 2018 | 127 | 2018 |
| An easy-to-hard learning paradigm for multiple classes and multiple labels W Liu, IW Tsang, M Klaus-Robert Journal of Machine Learning Research 18 (94), 1-38, 2017 | 115 | 2017 |
| Large margin metric learning for multi-label prediction W Liu, I Tsang Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015 | 108 | 2015 |
| Multiview discrete hashing for scalable multimedia search X Shen, F Shen, L Liu, YH Yuan, W Liu, QS Sun ACM Transactions on Intelligent Systems and Technology (TIST) 9 (5), 1-21, 2018 | 98 | 2018 |
| Making decision trees feasible in ultrahigh feature and label dimensions W Liu, IW Tsang Journal of Machine Learning Research 18 (81), 1-36, 2017 | 98 | 2017 |
| Discriminative and Correlative Partial Multi-Label Learning. H Wang, W Liu, Y Zhao, C Zhang, T Hu, G Chen IJCAI, 3691-3697, 2019 | 97 | 2019 |
| On the optimality of classifier chain for multi-label classification W Liu, I Tsang Advances in Neural Information Processing Systems 28, 2015 | 91 | 2015 |
| Compressed k-means for large-scale clustering X Shen, W Liu, I Tsang, F Shen, QS Sun Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 84 | 2017 |
| Multilabel prediction via cross-view search X Shen, W Liu, IW Tsang, QS Sun, YS Ong IEEE transactions on neural networks and learning systems 29 (9), 4324-4338, 2017 | 78 | 2017 |
| Discrete network embedding X Shen, S Pan, W Liu, YS Ong, QS Sun 27th International Joint Conference on Artificial Intelligence (IJCAI), 2018 | 76 | 2018 |
| Ddgr: Continual learning with deep diffusion-based generative replay R Gao, W Liu International Conference on Machine Learning, 10744-10763, 2023 | 57 | 2023 |
| On the tradeoff between robustness and fairness X Ma, Z Wang, W Liu Advances in Neural Information Processing Systems 35, 26230-26241, 2022 | 51 | 2022 |
| Two-stage label embedding via neural factorization machine for multi-label classification C Chen, H Wang, W Liu, X Zhao, T Hu, G Chen Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 3304-3311, 2019 | 48 | 2019 |
| Two-stage label embedding via neural factorization machine for multi-label classification C Chen, H Wang, W Liu, X Zhao, T Hu, G Chen Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 3304-3311, 2019 | 48 | 2019 |
| A dynamic evolutionary clustering perspective: Community detection in signed networks by reconstructing neighbor sets J Chen, H Wang, L Wang, W Liu Physica A: Statistical Mechanics and its Applications 447, 482-492, 2016 | 43 | 2016 |
| Sparse Embedded -Means Clustering W Liu, X Shen, I Tsang Advances in neural information processing systems 30, 2017 | 42 | 2017 |
| Collaboration based multi-label propagation for fraud detection H Wang, Z Li, J Huang, P Hui, W Liu, T Hu, G Chen Proceedings of the Twenty-Ninth International Conference on International …, 2021 | 31 | 2021 |
| Effectively predicting whether and when a topic will become prevalent in a social network W Liu, ZH Deng, X Gong, F Jiang, IW Tsang AAAI Conference on Artificial Intelligence (AAAI), 210-216, 2015 | 31 | 2015 |
Ivor W. Tsang, IEEE FellowInaugural A*STAR AI Fellow and Director, Centre for Frontier AI Research, A*STARVerificeret mail på cfar.a-star.edu.sg
