A General Knowledge Distillation Framework for Counterfactual Recommendation via Uniform Data D Liu, P Cheng, Z Dong, X He, W Pan, Z Ming Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020 | 205 | 2020 |
Mitigating Confounding Bias in Recommendation via Information Bottleneck D Liu, P Cheng, H Zhu, Z Dong, X He, W Pan, Z Ming Fifteenth ACM Conference on Recommender Systems, 351-360, 2021 | 97 | 2021 |
MetaSelector: Meta-Learning for Recommendation with User-Level Adaptive Model Selection M Luo, F Chen, P Cheng, Z Dong, X He, J Feng, Z Li Proceedings of The Web Conference 2020, 2507-2513, 2020 | 75 | 2020 |
KDCRec: Knowledge distillation for counterfactual recommendation via uniform data D Liu, P Cheng, Z Lin, J Luo, Z Dong, X He, W Pan, Z Ming IEEE Transactions on Knowledge and Data Engineering 35 (8), 8143-8156, 2022 | 21 | 2022 |
Counterfactual learning for recommender system Z Dong, H Zhu, P Cheng, X Feng, G Cai, X He, J Xu, J Wen Fourteenth ACM Conference on Recommender Systems, 568-569, 2020 | 19 | 2020 |
Debiased representation learning in recommendation via information bottleneck D Liu, P Cheng, H Zhu, Z Dong, X He, W Pan, Z Ming ACM Transactions on Recommender Systems 1 (1), 1-27, 2023 | 18 | 2023 |
DIWIFT: Discovering instance-wise influential features for tabular data D Liu, P Cheng, H Zhu, X Tang, Y Chen, X Wang, W Pan, Z Ming, X He Proceedings of the ACM Web Conference 2023, 1673-1682, 2023 | 7 | 2023 |
Bounding system-induced biases in recommender systems with a randomized dataset D Liu, P Cheng, Z Lin, X Zhang, Z Dong, R Zhang, X He, W Pan, Z Ming ACM Transactions on Information Systems 41 (4), 1-26, 2023 | 7 | 2023 |
Neural network distillation method and apparatus P Cheng, D Zhenhua, X He, X Zhang, S Yin, Y Hu US Patent App. 18/157,277, 2023 | 1 | 2023 |
DIWIFT: Discovering Instance-wise Influential Features for Tabular Data P Cheng, H Zhu, X Tang, D Liu, Y Chen, X Wang, W Pan, Z Ming, X He arXiv e-prints, arXiv: 2207.02773, 2022 | | 2022 |