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 | 60 | 2023 |
Causal disentanglement for semantic-aware intent learning in recommendation X Wang, Q Li, D Yu, P Cui, Z Wang, G Xu IEEE Transactions on Knowledge and Data Engineering 35 (10), 9836-9849, 2022 | 37 | 2022 |
Popularity prediction of movies: from statistical modeling to machine learning techniques SMR Abidi, Y Xu, J Ni, X Wang, W Zhang Multimedia Tools and Applications 79, 35583-35617, 2020 | 36 | 2020 |
ThermoEPred-EL: Robust bandgap predictions of chalcogenides with diamond-like structure via feature cross-based stacked ensemble learning X Wang, Y Xu, J Yang, J Ni, W Zhang, W Zhu Computational Materials Science 169, 109117, 2019 | 19 | 2019 |
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 | 13 | 2024 |
Joint relational dependency learning for sequential recommendation X Wang, Q Li, W Zhang, G Xu, S Liu, W Zhu Advances in Knowledge Discovery and Data Mining: 24th Pacific-Asia …, 2020 | 13 | 2020 |
New materials band gap prediction based on the high-throughput calculation and the machine learning XU YongLin, W XiangMeng, LI Xin, XI LiLi, NI JianYue, ZHU WenHao, ... Scientia Sinica Technologica 49 (1), 44-54, 2018 | 12 | 2018 |
Deconfounded recommendation via causal intervention D Yu, Q Li, X Wang, G Xu Neurocomputing 529, 128-139, 2023 | 11 | 2023 |
Mgpolicy: Meta graph enhanced off-policy learning for recommendations X Wang, Q Li, D Yu, Z Wang, H Chen, G Xu Proceedings of the 45th International ACM SIGIR Conference on Research and …, 2022 | 10 | 2022 |
SEHC: A high-throughput materials computing framework with automatic self-evaluation filtering W Zhu, Y Xu, J Ni, G Hu, X Wang, W Zhang Materials Science and Engineering: B 252, 114474, 2020 | 10 | 2020 |
Off-policy learning over heterogeneous information for recommendation X Wang, Q Li, D Yu, G Xu Proceedings of the ACM Web Conference 2022, 2348-2359, 2022 | 8 | 2022 |
Counterfactual explainable conversational recommendation D Yu, Q Li, X Wang, Q Li, G Xu IEEE Transactions on Knowledge and Data Engineering, 2023 | 7 | 2023 |
Counterfactual explanation for fairness in recommendation X Wang, Q Li, D Yu, Q Li, G Xu ACM Transactions on Information Systems 42 (4), 1-30, 2024 | 5 | 2024 |
Semantics-guided disentangled learning for recommendation D Yu, Q Li, X Wang, Z Wang, Y Cao, G Xu Pacific-Asia Conference on Knowledge Discovery and Data Mining, 249-261, 2022 | 5 | 2022 |
Demystifying help-seeking students interacting multimodal learning environment under machine learning regime SMR Abidi, J Ni, S Ge, X Wang, H Ding, W Zhu, W Zhang Eleventh International Conference on Graphics and Image Processing (ICGIP …, 2020 | 5 | 2020 |
Neural Causal Graph Collaborative Filtering X Wang, Q Li, D Yu, W Huang, Q Li, G Xu Information Sciences, 120872, 2024 | 4* | 2024 |
Prediction of teacher enrollment for Pakistani schools by using SVM S Kausar, X Huahu, MS Iqbal, X Wang, MY Shabir, T Khan International Journal of Information and Education Technology 9 (10), 710-714, 2019 | 3 | 2019 |
Constrained off-policy learning over heterogeneous information for fairness-aware recommendation X Wang, Q Li, D Yu, Q Li, G Xu ACM Transactions on Recommender Systems 2 (4), 1-27, 2024 | 2 | 2024 |
基于高通量计算及机器学习的新材料带隙预测 徐永林, 王香蒙, 李鑫, 席丽丽, 倪剑樾, 朱文浩, 张武, 杨炯 Chinese Science Bulletin 59, 1652, 2014 | 2 | 2014 |