| Attributed graph clustering via adaptive graph convolution X Zhang, H Liu, Q Li, XM Wu IJCAI 2019, 4327-4333, 2019 | 329 | 2019 |
| Label Efficient Semi-Supervised Learning via Graph Filtering Q Li, XM Wu, H Liu, X Zhang, Z Guan CVPR 2019, 9582-9591, 2019 | 213 | 2019 |
| Unknown intent detection using Gaussian mixture model with an application to zero-shot intent classification G Yan, L Fan, Q Li, H Liu, X Zhang, XM Wu, AYS Lam Proceedings of the 58th annual meeting of the association for computational …, 2020 | 86 | 2020 |
| Multi-task multi-view clustering X Zhang, X Zhang, H Liu, X Liu IEEE Transactions on Knowledge and Data Engineering 28 (12), 3324-3338, 2016 | 83 | 2016 |
| Deep anomaly detection with self-supervised learning and adversarial training X Zhang, J Mu, X Zhang, H Liu, L Zong, Y Li Pattern Recognition 121, 108234, 2022 | 72 | 2022 |
| Spectral embedding network for attributed graph clustering X Zhang, H Liu, XM Wu, X Zhang, X Liu Neural Networks 142, 388-396, 2021 | 48 | 2021 |
| Multi-task multi-view clustering for non-negative data X Zhang, X Zhang, H Liu Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015 | 47 | 2015 |
| Smart multi-task Bregman clustering and multi-task kernel clustering XZ Xianchao Zhang AAAI 2013, 1034-1040, 2013 | 46* | 2013 |
| Reconstructing capsule networks for zero-shot intent classification H Liu, X Zhang, L Fan, X Fu, Q Li, XM Wu, AYS Lam Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 45 | 2019 |
| Novel density-based and hierarchical density-based clustering algorithms for uncertain data X Zhang, H Liu, X Zhang Neural networks 93, 240-255, 2017 | 42 | 2017 |
| Self-Adapted Multi-Task Clustering. X Zhang, X Zhang, H Liu IJCAI, 2357-2363, 2016 | 36 | 2016 |
| Personalized knowledge-aware recommendation with collaborative and attentive graph convolutional networks Q Dai, XM Wu, L Fan, Q Li, H Liu, X Zhang, D Wang, G Lin, K Yang Pattern Recognition 128, 108628, 2022 | 33 | 2022 |
| Multi-task clustering through instances transfer X Zhang, X Zhang, H Liu, X Liu Neurocomputing 251, 145-155, 2017 | 28 | 2017 |
| Self-adapted mixture distance measure for clustering uncertain data H Liu, X Zhang, X Zhang, Y Cui Knowledge-Based Systems 126, 33-47, 2017 | 27 | 2017 |
| Multi-Task Clustering with Model Relation Learning. X Zhang, X Zhang, H Liu, J Luo IJCAI, 3132-3140, 2018 | 24 | 2018 |
| An explicit-joint and supervised-contrastive learning framework for few-shot intent classification and slot filling H Liu, F Zhang, X Zhang, S Zhao, X Zhang arXiv preprint arXiv:2110.13691, 2021 | 22 | 2021 |
| Partially related multi-task clustering X Zhang, X Zhang, H Liu, X Liu IEEE Transactions on Knowledge and Data Engineering 30 (12), 2367-2380, 2018 | 21 | 2018 |
| Label-enhanced prototypical network with contrastive learning for multi-label few-shot aspect category detection H Liu, F Zhang, X Zhang, S Zhao, J Sun, H Yu, X Zhang Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 20 | 2022 |
| PwAdaBoost: Possible world based AdaBoost algorithm for classifying uncertain data H Liu, X Zhang, X Zhang Knowledge-Based Systems 186, 104930, 2019 | 19 | 2019 |
| Possible world based consistency learning model for clustering and classifying uncertain data H Liu, X Zhang, X Zhang Neural Networks 102, 48-66, 2018 | 18 | 2018 |
Han LiuAssociate Professor, Dalian University of TechnologyVerified email at dlut.edu.cn