| Deepfm: A factorization-machine based neural network for CTR prediction H Guo, R Tang, Y Ye, Z Li, X He IJCAI (The most cited paper of IJCAI in the past 5 years), 1725-1731, 2017 | 2819 | 2017 |
| Product-based neural networks for user response prediction over multi-field categorical data Y Qu, B Fang, W Zhang, R Tang, M Niu, H Guo, Y Yu, X He ACM Transactions on Information Systems (TOIS) 37 (1), 1-35, 2018 | 222 | 2018 |
| Feature generation by convolutional neural network for click-through rate prediction B Liu, R Tang, Y Chen, J Yu, H Guo, Y Zhang The World Wide Web Conference, 1119-1129, 2019 | 163 | 2019 |
| Neighbor interaction aware graph convolution networks for recommendation J Sun, Y Zhang, W Guo, H Guo, R Tang, X He, C Ma, M Coates Proceedings of the 43rd international ACM SIGIR conference on research and …, 2020 | 152 | 2020 |
| Deep reinforcement learning based recommendation with explicit user-item interactions modeling F Liu, R Tang, X Li, W Zhang, Y Ye, H Chen, H Guo, Y Zhang arXiv preprint arXiv:1810.12027, 2018 | 149 | 2018 |
| Multi-graph convolution collaborative filtering J Sun, Y Zhang, C Ma, M Coates, H Guo, R Tang, X He 2019 IEEE International Conference on Data Mining (ICDM), 1306-1311, 2019 | 139 | 2019 |
| An embedding learning framework for numerical features in ctr prediction H Guo, B Chen, R Tang, W Zhang, Z Li, X He Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 89 | 2021 |
| Graphsail: Graph structure aware incremental learning for recommender systems Y Xu, Y Zhang, W Guo, H Guo, R Tang, M Coates Proceedings of the 29th ACM International Conference on Information …, 2020 | 82 | 2020 |
| A framework for recommending accurate and diverse items using bayesian graph convolutional neural networks J Sun, W Guo, D Zhang, Y Zhang, F Regol, Y Hu, H Guo, R Tang, H Yuan, ... Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 82 | 2020 |
| Deepfm: An end-to-end wide & deep learning framework for CTR prediction H Guo, R Tang, Y Ye, Z Li, X He, Z Dong arXiv preprint arXiv:1804.04950, 2018 | 78 | 2018 |
| DSKmeans: a new kmeans-type approach to discriminative subspace clustering X Huang, Y Ye, H Guo, Y Cai, H Zhang, Y Li Knowledge-Based Systems 70, 293-300, 2014 | 73 | 2014 |
| PAL: a position-bias aware learning framework for CTR prediction in live recommender systems H Guo, J Yu, Q Liu, R Tang, Y Zhang Proceedings of the 13th ACM Conference on Recommender Systems, 452-456, 2019 | 71 | 2019 |
| State representation modeling for deep reinforcement learning based recommendation F Liu, R Tang, X Li, W Zhang, Y Ye, H Chen, H Guo, Y Zhang, X He Knowledge-Based Systems 205, 106170, 2020 | 60 | 2020 |
| Dual graph enhanced embedding neural network for CTR prediction W Guo, R Su, R Tan, H Guo, Y Zhang, Z Liu, R Tang, X He Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data …, 2021 | 56 | 2021 |
| AutoGroup: Automatic feature grouping for modelling explicit high-order feature interactions in CTR prediction B Liu, N Xue, H Guo, R Tang, S Zafeiriou, X He, Z Li Proceedings of the 43rd international ACM SIGIR conference on research and …, 2020 | 52 | 2020 |
| Multi-behavior sequential transformer recommender E Yuan, W Guo, Z He, H Guo, C Liu, R Tang Proceedings of the 45th international ACM SIGIR conference on research and …, 2022 | 47 | 2022 |
| End-to-end deep reinforcement learning based recommendation with supervised embedding F Liu, H Guo, X Li, R Tang, Y Ye, X He Proceedings of the 13th International Conference on Web Search and Data …, 2020 | 45 | 2020 |
| Learning binarized graph representations with multi-faceted quantization reinforcement for top-k recommendation Y Chen, H Guo, Y Zhang, C Ma, R Tang, J Li, I King Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 32 | 2022 |
| A practical incremental method to train deep ctr models Y Wang, H Guo, R Tang, Z Liu, X He arXiv preprint arXiv:2009.02147, 2020 | 31 | 2020 |
| Miss: Multi-interest self-supervised learning framework for click-through rate prediction W Guo, C Zhang, Z He, J Qin, H Guo, B Chen, R Tang, X He, R Zhang 2022 IEEE 38th international conference on data engineering (ICDE), 727-740, 2022 | 30 | 2022 |
Ruiming TangHuawei在 huawei.com 的电子邮件经过验证
