| Patient subtyping via time-aware LSTM networks IM Baytas, C Xiao, X Zhang, F Wang, AK Jain, J Zhou Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 2017 | 679 | 2017 |
| Differentially private generative adversarial network L Xie, K Lin, S Wang, F Wang, J Zhou arXiv preprint arXiv:1802.06739, 2018 | 555 | 2018 |
| Data-free knowledge distillation for heterogeneous federated learning Z Zhu, J Hong, J Zhou International conference on machine learning, 12878-12889, 2021 | 512 | 2021 |
| Transfer learning in deep reinforcement learning: A survey Z Zhu, K Lin, AK Jain, J Zhou IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 | 492 | 2023 |
| Efficient large-scale fleet management via multi-agent deep reinforcement learning K Lin, R Zhao, Z Xu, J Zhou Proceedings of the 24th ACM SIGKDD international conference on knowledge …, 2018 | 457 | 2018 |
| Malsar: Multi-task learning via structural regularization J Zhou, J Chen, J Ye Arizona State University 21, 1-50, 2011 | 393 | 2011 |
| Graph convolutional networks for computational drug development and discovery M Sun, S Zhao, C Gilvary, O Elemento, J Zhou, F Wang Briefings in bioinformatics 21 (3), 919-935, 2020 | 348 | 2020 |
| Clustered multi-task learning via alternating structure optimization J Zhou, J Chen, J Ye Advances in neural information processing systems 24, 2011 | 318 | 2011 |
| A multi-task learning formulation for predicting disease progression J Zhou, L Yuan, J Liu, J Ye Proceedings of the 17th ACM SIGKDD international conference on Knowledge …, 2011 | 274 | 2011 |
| Integrating low-rank and group-sparse structures for robust multi-task learning J Chen, J Zhou, J Ye Proceedings of the 17th ACM SIGKDD international conference on Knowledge …, 2011 | 256 | 2011 |
| Lasso Screening Rules via Dual Polytope Projection J Wang, J Zhou, P Wonka, J Ye NIPS, 2013 | 245 | 2013 |
| Modeling disease progression via fused sparse group lasso J Zhou, J Liu, VA Narayan, J Ye Proceedings of the 18th ACM SIGKDD international conference on Knowledge …, 2012 | 230 | 2012 |
| Modeling disease progression via multi-task learning J Zhou, J Liu, VA Narayan, J Ye, ... NeuroImage 78, 233-248, 2013 | 229 | 2013 |
| Analysis of sampling techniques for imbalanced data: An n= 648 ADNI study R Dubey, J Zhou, Y Wang, PM Thompson, J Ye, ... NeuroImage 87, 220-241, 2014 | 222 | 2014 |
| Missing modalities imputation via cascaded residual autoencoder L Tran, X Liu, J Zhou, R Jin Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 197 | 2017 |
| Drug similarity integration through attentive multi-view graph auto-encoders T Ma, C Xiao, J Zhou, F Wang arXiv preprint arXiv:1804.10850, 2018 | 188 | 2018 |
| An rnn architecture with dynamic temporal matching for personalized predictions of parkinson's disease C Che, C Xiao, J Liang, B Jin, J Zho, F Wang Proceedings of the 2017 SIAM international conference on data mining, 198-206, 2017 | 153 | 2017 |
| From micro to macro: data driven phenotyping by densification of longitudinal electronic medical records J Zhou, F Wang, J Hu, J Ye Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014 | 150 | 2014 |
| Comparison of nine tractography algorithms for detecting abnormal structural brain networks in Alzheimer’s disease L Zhan, J Zhou, Y Wang, Y Jin, N Jahanshad, G Prasad, TM Nir, ... Frontiers in aging neuroscience 7, 48, 2015 | 149 | 2015 |
| GCN-MF: disease-gene association identification by graph convolutional networks and matrix factorization P Han, P Yang, P Zhao, S Shang, Y Liu, J Zhou, X Gao, P Kalnis Proceedings of the 25th ACM SIGKDD international conference on knowledge …, 2019 | 147 | 2019 |
Jieping Ye, IEEE Fellow & ACM Distin...Alibaba Group在 umich.edu 的电子邮件经过验证
