| Wasserstein distance guided representation learning for domain adaptation J Shen, Y Qu, W Zhang, Y Yu Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 889 | 2018 |
| Product-based neural networks for user response prediction Y Qu, H Cai, K Ren, W Zhang, Y Yu, Y Wen, J Wang 2016 IEEE 16th international conference on data mining (ICDM), 1149-1154, 2016 | 712 | 2016 |
| Dynamically fused graph network for multi-hop reasoning L Qiu, Y Xiao, Y Qu, H Zhou, L Li, W Zhang, Y Yu Proceedings of the 57th annual meeting of the association for computational …, 2019 | 240 | 2019 |
| 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 | 213 | 2018 |
| A simple but tough-to-beat data augmentation approach for natural language understanding and generation D Shen, M Zheng, Y Shen, Y Qu, W Chen arXiv preprint arXiv:2009.13818, 2020 | 126 | 2020 |
| GIKT: a graph-based interaction model for knowledge tracing Y Yang, J Shen, Y Qu, Y Liu, K Wang, Y Zhu, W Zhang, Y Yu Machine Learning and Knowledge Discovery in Databases: European Conference …, 2021 | 125 | 2021 |
| Label-aware double transfer learning for cross-specialty medical named entity recognition Z Wang, Y Qu, L Chen, J Shen, W Zhang, S Zhang, Y Gao, G Gu, K Chen, ... arXiv preprint arXiv:1804.09021, 2018 | 88 | 2018 |
| Coda: Contrast-enhanced and diversity-promoting data augmentation for natural language understanding Y Qu, D Shen, Y Shen, S Sajeev, J Han, W Chen arXiv preprint arXiv:2010.08670, 2020 | 87 | 2020 |
| An end-to-end neighborhood-based interaction model for knowledge-enhanced recommendation Y Qu, T Bai, W Zhang, J Nie, J Tang Proceedings of the 1st international workshop on deep learning practice for …, 2019 | 60 | 2019 |
| Multi-document summarization with maximal marginal relevance-guided reinforcement learning Y Mao, Y Qu, Y Xie, X Ren, J Han arXiv preprint arXiv:2010.00117, 2020 | 40 | 2020 |
| QA4IE: A question answering based framework for information extraction L Qiu, H Zhou, Y Qu, W Zhang, S Li, S Rong, D Ru, L Qian, K Tu, Y Yu The Semantic Web–ISWC 2018: 17th International Semantic Web Conference …, 2018 | 19* | 2018 |
| Event time extraction and propagation via graph attention networks H Wen, Y Qu, H Ji, Q Ning, J Han, A Sil, H Tong, D Roth Proceedings of the 2021 Conference of the North American Chapter of the …, 2021 | 18 | 2021 |
| MAP: A Model-agnostic Pretraining Framework for Click-through Rate Prediction J Lin, Y Qu, W Guo, X Dai, R Tang, Y Yu, W Zhang Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 10 | 2023 |
| Task-wise split gradient boosting trees for multi-center diabetes prediction M Chen, Z Wang, Z Zhao, W Zhang, X Guo, J Shen, Y Qu, J Lu, M Xu, ... Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 9 | 2021 |
| Collaborative filtering with graph-based implicit feedback M Niu, R Tang, Y Qu, X He, X Cao, Y Yu 2018 IEEE 3rd International Conference on Cloud Computing and Internet of …, 2018 | 4 | 2018 |
| TGE-PS: Text-driven Graph Embedding with Pairs Sampling L Chen, Y Qu, Z Wang, L Qiu, W Zhang, K Chen, S Zhang, Y Yu | 2* | 2019 |
| ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Prediction J Lin, B Chen, H Wang, Y Xi, Y Qu, X Dai, K Zhang, R Tang, Y Yu, ... arXiv preprint arXiv:2310.09234, 2023 | | 2023 |
| User behavior prediction method and apparatus, and behavior prediction model training method and apparatus R Tang, NIU Minzhe, QU Yanru, W Zhang, Y Yu US Patent 11,531,867, 2022 | | 2022 |
| MT-GBDT: Multi-Task Gradient Boosting Decision Tree for Diabetes Prediction Z Wang, Y Qu, G Sui, J Shen, W Zhang, Z Zhao, G Ning, Y Yu | | |
Weinan ZhangAssociate Professor, Shanghai Jiao Tong Universitysjtu.edu.cn의 이메일 확인됨
