Joint entity linking with deep reinforcement learning Z Fang, Y Cao, Q Li, D Zhang, Z Zhang, Y Liu The World Wide Web Conference, 438-447, 2019 | 108 | 2019 |
Be causal: De-biasing social network confounding in recommendation Q Li, X Wang, Z Wang, G Xu ACM Transactions on Knowledge Discovery from Data 17 (1), 1-23, 2023 | 57 | 2023 |
How does knowledge graph embedding extrapolate to unseen data: a semantic evidence view R Li, Y Cao, Q Zhu, G Bi, F Fang, Y Liu, Q Li Proceedings of the AAAI Conference on Artificial Intelligence 36 (5), 5781-5791, 2022 | 46 | 2022 |
Causality Learning: A New Perspective for Interpretable Machine Learning G Xu, TD Duong, Q Li, S Liu, X Wang The IEEE Intelligent Informatics Bulletin 20, 2020 | 46 | 2020 |
Causal Disentanglement for Semantics-Aware Intent Learning in Recommendation X Wang, Q Li, D Yu, P Cui, Z Wang, G Xu IEEE Transactions on Knowledge and Data Engineering, 2022 | 32 | 2022 |
RLINK: Deep reinforcement learning for user identity linkage X Li, Y Cao, Q Li, Y Shang, Y Li, Y Liu, G Xu World Wide Web 24, 85-103, 2021 | 26 | 2021 |
Learning with privileged information for photo aesthetic assessment Y Shu, Q Li, S Liu, G Xu Neurocomputing 404, 304-316, 2020 | 25 | 2020 |
Causal optimal transport for treatment effect estimation Q Li, Z Wang, S Liu, G Li, G Xu IEEE transactions on neural networks and learning systems 34 (8), 4083-4095, 2021 | 24 | 2021 |
Leveraging multi-level dependency of relational sequences for social spammer detection J Yin, Q Li, S Liu, Z Wu, G Xu Neurocomputing 428, 130-141, 2021 | 24 | 2021 |
Polynomial representation for persistence diagram Z Wang, Q Li, G Li, G Xu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 18 | 2019 |
Boosting imbalanced data learning with Wiener process oversampling Q Li, G Li, W Niu, Y Cao, L Chang, J Tan, L Guo Frontiers of Computer Science 11, 836-851, 2017 | 16 | 2017 |
Prototype-based Counterfactual Explanation for Causal Classification TD Duong, Q Li, G Xu arXiv preprint arXiv:2105.00703, 2021 | 14 | 2021 |
Riemannian submanifold tracking on low-rank algebraic variety Q Li, Z Wang Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 14 | 2017 |
Lingo: linearized grassmannian optimization for nuclear norm minimization Q Li, W Niu, G Li, Y Cao, J Tan, L Guo Proceedings of the 24th ACM International on Conference on Information and …, 2015 | 14 | 2015 |
Deep treatment-adaptive network for causal inference Q Li, Z Wang, S Liu, G Li, G Xu The VLDB Journal 31 (5), 1127-1142, 2022 | 13 | 2022 |
Hilbert Sinkhorn Divergence for Optimal Transport Q Li, Z Wang, G Li, J Pang, G Xu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 13 | 2021 |
Joint Relational Dependency Learning for Sequential Recommendation X Wang, Q Li, W Zhang, G Xu, S Liu, W Zhu Pacific-Asia Conference on Knowledge Discovery and Data Mining, 168-180, 2020 | 13 | 2020 |
Reinforced path reasoning for counterfactual explainable recommendation X Wang, Q Li, D Yu, Q Li, G Xu IEEE Transactions on Knowledge and Data Engineering, 2024 | 12 | 2024 |
SGCCL: Siamese Graph Contrastive Consensus Learning for Personalized Recommendation B Li, T Guo, X Zhu, Q Li, Y Wang, F Chen Proceedings of the Sixteenth ACM International Conference on Web Search and …, 2023 | 12 | 2023 |
Stochastic Intervention for Causal Effect Estimation TD Duong, Q Li, G Xu IJCNN 2021: International Joint Conference on Neural Networks, 2021 | 12 | 2021 |