| 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, 2020 | 6490 | 2020 |
| 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 34 (8), 3549-3568, 2020 | 1051 | 2020 |
| Parallel K-Means Clustering Based on MapReduce W Zhao, H Ma, Q He Cloud Computing: First International Conference, CloudCom 2009, Beijing …, 2009 | 988 | 2009 |
| 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 | 929 | 2020 |
| 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 | 481 | 2015 |
| Pick and choose: a GNN-based imbalanced learning approach for fraud detection Y Liu, X Ao, Z Qin, J Chi, J Feng, H Yang, Q He Proceedings of the web conference 2021, 3168-3177, 2021 | 345 | 2021 |
| Parallel implementation of apriori algorithm based on mapreduce N Li, L Zeng, Q He, Z Shi International Journal of Networked and Distributed Computing 1 (2), 89-96, 2013 | 257 | 2013 |
| 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 | 247 | 2019 |
| 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 | 226 | 2020 |
| Survey on transfer learning research 庄福振， 罗平， 何清， 史忠植 Journal of Software 26 (1), 26-39, 2014 | 222 | 2014 |
| 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 | 216 | 2022 |
| Warm up cold-start advertisements: Improving ctr predictions via learning to learn id embeddings F Pan, S Li, X Ao, P Tang, Q He Proceedings of the 42nd International ACM SIGIR Conference on Research and …, 2019 | 212 | 2019 |
| Chinesebert: Chinese pretraining enhanced by glyph and pinyin information Z Sun, X Li, X Sun, Y Meng, X Ao, Q He, F Wu, J Li arXiv preprint arXiv:2106.16038, 2021 | 211 | 2021 |
| Parallel extreme learning machine for regression based on MapReduce Q He, T Shang, F Zhuang, Z Shi Neurocomputing 102, 52-58, 2013 | 190 | 2013 |
| Intelligent financial fraud detection practices in post-pandemic era X Zhu, X Ao, Z Qin, Y Chang, Y Liu, Q He, J Li The Innovation 2 (4), 2021 | 171 | 2021 |
| Extreme support vector machine classifier Q Liu, Q He, Z Shi Advances in Knowledge Discovery and Data Mining: 12th Pacific-Asia …, 2008 | 151 | 2008 |
| 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 | 140 | 2008 |
| Transfer-meta framework for cross-domain recommendation to cold-start users Y Zhu, K Ge, F Zhuang, R Xie, D Xi, X Zhang, L Lin, Q He Proceedings of the 44th international ACM SIGIR conference on research and …, 2021 | 133 | 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 | 128 | 2011 |
| 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 | 125 | 2017 |
Fuzhen Zhuang (庄福振)Professor at Institute of Artificial Intelligence, Beihang UniversityDirección de correo verificada de buaa.edu.cn