| A Deep Latent Factor Model for High-Dimensional and Sparse Matrices in Recommender Systems D Wu, L Xin, M Shang, Y He, G Wang, MC Zhou IEEE Transactions on Systems, Man and Cybernetics: Systems, 2019 | 99 | 2019 |
| A data-characteristic-aware latent factor model for web services QoS prediction D Wu, X Luo, M Shang, Y He, G Wang, X Wu IEEE Transactions on Knowledge and Data Engineering, 2020 | 63 | 2020 |
| A posterior-neighborhood-regularized latent factor model for highly accurate web service QoS prediction D Wu, Q He, X Luo, M Shang, Y He, G Wang IEEE Transactions on Services Computing, 2019 | 43 | 2019 |
| A latent factor analysis-based approach to online sparse streaming feature selection D Wu, Y He, X Luo, MC Zhou IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021 | 30 | 2021 |
| Online Learning from Capricious Data Streams: A Generative Approach Y He, B Wu, D Wu, E Beyazit, S Chen, X Wu the 28th International Joint Conference on Artificial Intelligence, 2019 | 18 | 2019 |
| Toward mining capricious data streams: A generative approach Y He, B Wu, D Wu, E Beyazit, S Chen, X Wu IEEE transactions on neural networks and learning systems 32 (3), 1228-1240, 2020 | 15 | 2020 |
| A data-aware latent factor model for Web service QoS prediction D Wu, X Luo, M Shang, Y He, G Wang, X Wu Pacific-Asia Conference on Knowledge Discovery and Data Mining, 384-399, 2019 | 14 | 2019 |
| Online feature selection with capricious streaming features: A general framework D Wu, Y He, X Luo, M Shang, X Wu 2019 IEEE International Conference on Big Data (Big Data), 683-688, 2019 | 8 | 2019 |
| Online learning in variable feature spaces under incomplete supervision Y He, X Yuan, S Chen, X Wu AAAI 35 (5), 4106-4114, 2021 | 6 | 2021 |
| Online streaming feature selection via conditional independence D You, X Wu, L Shen, Y He, X Yuan, Z Chen, S Deng, C Ma Applied Sciences 8 (12), 2548, 2018 | 6 | 2018 |
| Generating Precise Error Specifications for C: A Zero Shot Learning Approach B Wu, J Campora, Y He, A Schlecht, S Chen OOPSLA 2019, 2019 | 5 | 2019 |
| Supervised data synthesizing and evolving–a framework for real-world traffic crash severity classification Y He, D Wu, E Beyazit, X Sun, X Wu 2018 IEEE 30th International Conference on Tools with Artificial …, 2018 | 5 | 2018 |
| On Partial Multi-Task Learning Y He, B Wu, D Wu, X Wu ECAI 2020 325, 1174 - 1181, 0 | 3* | |
| Unsupervised Lifelong Learning with Curricula Y He, S Chen, B Wu, X Yuan, X Wu Proceedings of the Web Conference 2021, 3534-3545, 2021 | 2 | 2021 |
| Online Learning in Variable Feature Spaces with Mixed Data Y He, J Dong, BJ Hou, Y Wang, F Wang 2021 IEEE International Conference on Data Mining (ICDM), 181-190, 2021 | 1 | 2021 |
| Privacy-Preserving Multi-Granular Federated Neural Architecture Search A General Framework Z Pan, L Hu, W Tang, J Li, Y He, Z Liu IEEE Transactions on Knowledge and Data Engineering, 2021 | 1 | 2021 |
| Deep matrix tri-factorization: Mining vertex-wise interactions in multi-space attributed graphs Y He, S Chen, T Nguyen, BA Wade, X Wu Proceedings of the 2020 SIAM International Conference on Data Mining, 334-342, 2020 | 1 | 2020 |
| A Quantitative Risk Assessment Model for Distribution Cyber Physical System under Cyber Attack S Deng, J Zhang, D Wu, Y He, X Xie, X Wu IEEE Transactions on Industrial Informatics, 2022 | | 2022 |
| Online Deep Learning from Doubly-Streaming Data H Lian, JS Atwood, B Hou, J Wu, Y He arXiv preprint arXiv:2204.11793, 2022 | | 2022 |
| Graph-incorporated Latent Factor Analysis for High-dimensional and Sparse Matrices D Wu, Y He, X Luo arXiv preprint arXiv:2204.07818, 2022 | | 2022 |
Xindong WuHefei University of TechnologyVerified email at hfut.edu.cn
