| A comprehensive survey on transfer learning F Zhuang, Z Qi, K Duan, D Xi, Y Zhu, H Zhu, H Xiong, Q He Proceedings of the IEEE 109 (1), 43-76, 2021 | 5006 | 2021 |
| A survey on knowledge graph-based recommender systems Q Guo, F Zhuang, C Qin, H Zhu, X Xie, H Xiong, Q He IEEE Transactions on Knowledge and Data Engineering, 2020 | 831 | 2020 |
| Deep subdomain adaptation network for image classification Y Zhu, F Zhuang, J Wang, G Ke, J Chen, J Bian, H Xiong, Q He IEEE transactions on neural networks and learning systems 32 (4), 1713-1722, 2020 | 695 | 2020 |
| Graph contextualized self-attention network for session-based recommendation. C Xu, P Zhao, Y Liu, VS Sheng, J Xu, F Zhuang, J Fang, X Zhou IJCAI 19, 3940-3946, 2019 | 572 | 2019 |
| Supervised representation learning: Transfer learning with deep autoencoders F Zhuang, X Cheng, P Luo, SJ Pan, Q He Twenty-fourth international joint conference on artificial intelligence, 2015 | 449 | 2015 |
| Where to go next: A spatio-temporal gated network for next poi recommendation P Zhao, A Luo, Y Liu, J Xu, Z Li, F Zhuang, VS Sheng, X Zhou IEEE Transactions on Knowledge and Data Engineering 34 (5), 2512-2524, 2020 | 427 | 2020 |
| Sequential recommender system based on hierarchical attention network H Ying, F Zhuang, F Zhang, Y Liu, G Xu, X Xie, H Xiong, J Wu IJCAI international joint conference on artificial intelligence, 2018 | 388 | 2018 |
| Aligning domain-specific distribution and classifier for cross-domain classification from multiple sources Y Zhu, F Zhuang, D Wang Proceedings of the AAAI conference on artificial intelligence 33 (01), 5989-5996, 2019 | 312 | 2019 |
| Multi-representation adaptation network for cross-domain image classification Y Zhu, F Zhuang, J Wang, J Chen, Z Shi, W Wu, Q He Neural Networks 119, 214-221, 2019 | 211 | 2019 |
| Survey on transfer learning research FZ Zhuang, P Luo, Q He, Z Shi Journal of software 26 (1), 26-39, 2015 | 209* | 2015 |
| 迁移学习研究进展 庄福振， 罗平， 何清， 史忠植 软件学报 26 (1), 26-39, 2015 | 197 | 2015 |
| Relational graph neural network with hierarchical attention for knowledge graph completion Z Zhang, F Zhuang, H Zhu, Z Shi, H Xiong, Q He Proceedings of the AAAI conference on artificial intelligence 34 (05), 9612-9619, 2020 | 194 | 2020 |
| Parallel extreme learning machine for regression based on MapReduce Q He, T Shang, F Zhuang, Z Shi Neurocomputing 102, 52-58, 2013 | 186 | 2013 |
| Personalized transfer of user preferences for cross-domain recommendation Y Zhu, Z Tang, Y Liu, F Zhuang, R Xie, X Zhang, L Lin, Q He Proceedings of the fifteenth ACM international conference on web search and …, 2022 | 151 | 2022 |
| Transfer learning from multiple source domains via consensus regularization P Luo, F Zhuang, H Xiong, Y Xiong, Q He Proceedings of the 17th ACM conference on Information and knowledge …, 2008 | 136 | 2008 |
| Promptbert: Improving bert sentence embeddings with prompts T Jiang, J Jiao, S Huang, Z Zhang, D Wang, F Zhuang, F Wei, H Huang, ... arXiv preprint arXiv:2201.04337, 2022 | 135 | 2022 |
| LightXML: Transformer with Dynamic Negative Sampling for High-Performance Extreme Multi-label Text Classification T Jiang, D Wang, L Sun, H Yang, Z Zhao, F Zhuang arXiv preprint arXiv:2101.03305, 2021 | 132 | 2021 |
| Exploiting associations between word clusters and document classes for cross‐domain text categorization F Zhuang, P Luo, H Xiong, Q He, Y Xiong, Z Shi Statistical Analysis and Data Mining: The ASA Data Science Journal 4 (1 …, 2011 | 120 | 2011 |
| Learning deep representations via extreme learning machines W Yu, F Zhuang, Q He, Z Shi Neurocomputing 149, 308-315, 2015 | 119 | 2015 |
| Representation learning via dual-autoencoder for recommendation F Zhuang, Z Zhang, M Qian, C Shi, X Xie, Q He Neural Networks 90, 83-89, 2017 | 118 | 2017 |
He QingInstitute of Computing Technology,Chinese Academy of Sciences在 ict.ac.cn 的电子邮件经过验证
