| 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 | 1968 | 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 | 171 | 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 | 122 | 2019 |
| 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 | 102 | 2018 |
| 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 | 99 | 2020 |
| 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 | 78 | 2019 |
| 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 | 65 | 2014 |
| 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 | 62 | 2018 |
| 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 | 61 | 2020 |
| 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 | 48* | 2021 |
| 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 | 47 | 2019 |
| 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 | 40 | 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 | 38 | 2021 |
| 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 | 37 | 2020 |
| 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 | 35 | 2020 |
| 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 | 34 | 2020 |
| Field-aware probabilistic embedding neural network for CTR prediction W Liu, R Tang, J Li, J Yu, H Guo, X He, S Zhang Proceedings of the 12th ACM Conference on Recommender Systems, 412-416, 2018 | 21 | 2018 |
| 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 | 17 | 2020 |
| Scalefreectr: Mixcache-based distributed training system for ctr models with huge embedding table H Guo, W Guo, Y Gao, R Tang, X He, W Liu Proceedings of the 44th international ACM SIGIR conference on research and …, 2021 | 16 | 2021 |
| Top-aware reinforcement learning based recommendation F Liu, R Tang, H Guo, X Li, Y Ye, X He Neurocomputing 417, 255-269, 2020 | 16 | 2020 |
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