| Pareto self-supervised training for few-shot learning Z Chen, J Ge, H Zhan, S Huang, D Wang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 92 | 2021 |
| Learning how to propagate messages in graph neural networks T Xiao, Z Chen, D Wang, S Wang Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 53 | 2021 |
| Deep transfer tensor decomposition with orthogonal constraint for recommender systems Z Chen, Z Xu, D Wang Proceedings of the AAAI conference on artificial intelligence 35 (5), 4010-4018, 2021 | 37 | 2021 |
| Ba-gnn: On learning bias-aware graph neural network Z Chen, T Xiao, K Kuang 2022 IEEE 38th International Conference on Data Engineering (ICDE), 3012-3024, 2022 | 36 | 2022 |
| Decoupled self-supervised learning for graphs T Xiao, Z Chen, Z Guo, Z Zhuang, S Wang Advances in Neural Information Processing Systems 35, 620-634, 2022 | 33 | 2022 |
| Multi-initialization meta-learning with domain adaptation Z Chen, D Wang ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 28 | 2021 |
| Deep tensor factorization for multi-criteria recommender systems Z Chen, S Gai, D Wang 2019 IEEE International Conference on Big Data (Big Data), 1046-1051, 2019 | 28 | 2019 |
| Duet: A tuning-free device-cloud collaborative parameters generation framework for efficient device model generalization Z Lv, W Zhang, S Zhang, K Kuang, F Wang, Y Wang, Z Chen, T Shen, ... Proceedings of the ACM Web Conference 2023, 3077-3085, 2023 | 27 | 2023 |
| Improving cold-start recommendation via multi-prior meta-learning Z Chen, D Wang, S Yin Advances in Information Retrieval: 43rd European Conference on IR Research …, 2021 | 21 | 2021 |
| Deep transfer collaborative filtering for recommender systems G Sibo, Z Feng, Y Kang, Z Chen, D Wang, A Tang Pacific Rim International Conference on Artificial Intelligence, 515-528, 2019 | 20* | 2019 |
| Learn goal-conditioned policy with intrinsic motivation for deep reinforcement learning J Liu, D Wang, Q Tian, Z Chen Proceedings of the AAAI conference on artificial intelligence 36 (7), 7558-7566, 2022 | 18 | 2022 |
| Sub-diffraction imaging using fourier ptychography and structured sparsity G Jagatap, Z Chen, C Hegde, N Vaswani 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 18 | 2018 |
| Low rank fourier ptychography Z Chen, G Jagatap, S Nayer, C Hegde, N Vaswani 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 17 | 2018 |
| Ideal: Toward high-efficiency device-cloud collaborative and dynamic recommendation system Z Lv, Z Chen, S Zhang, K Kuang, W Zhang, M Li, BC Ooi, F Wu arXiv preprint arXiv:2302.07335, 2023 | 13 | 2023 |
| The role of deconfounding in meta-learning Y Jiang, Z Chen, K Kuang, L Yuan, X Ye, Z Wang, F Wu, Y Wei International Conference on Machine Learning, 10161-10176, 2022 | 11 | 2022 |
| Global and local tensor factorization for multi-criteria recommender system S Wang, J Yang, Z Chen, H Yuan, J Geng, Z Hai Patterns 1 (2), 2020 | 11 | 2020 |
| End-to-end open-set semi-supervised node classification with out-of-distribution detection T Huang, D Wang, Y Fang, Z Chen IJCAI, 2022 | 10 | 2022 |
| Multi-scale gradient domain underwater image enhancement Z Mi, Z Liang, Y Wang, X Fu, Z Chen 2018 OCEANS-MTS/IEEE Kobe Techno-Oceans (OTO), 1-5, 2018 | 10 | 2018 |
| Representation matters when learning from biased feedback in recommendation T Xiao, Z Chen, S Wang Proceedings of the 31st ACM International Conference on Information …, 2022 | 9 | 2022 |
| Towards underwater object recognition based on supervised learning Z Chen, T Zhao, N Cheng, X Sun, X Fu 2018 OCEANS-MTS/IEEE Kobe Techno-Oceans (OTO), 1-4, 2018 | 9 | 2018 |
