| Deep multi-view spatial-temporal network for taxi demand prediction H Yao, F Wu, J Ke, X Tang, Y Jia, S Lu, P Gong, J Ye, Z Li Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 1291 | 2018 |
| A general iterative shrinkage and thresholding algorithm for non-convex regularized optimization problems P Gong, C Zhang, Z Lu, J Huang, J Ye The 30th International Conference on Machine Learning (ICML), 37-45, 2013 | 397 | 2013 |
| Robust Multi-Task Feature Learning P Gong, J Ye, C Zhang The 18th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2012 | 321 | 2012 |
| A taxi order dispatch model based on combinatorial optimization L Zhang, T Hu, Y Min, G Wu, J Zhang, P Feng, P Gong, J Ye Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 2017 | 265 | 2017 |
| Lasso screening rules via dual polytope projection J Wang, B Lin, P Gong, P Wonka, J Ye arXiv preprint arXiv:1211.3966, 2012 | 246 | 2012 |
| Learning from very few samples: A survey J Lu, P Gong, J Ye, C Zhang arXiv preprint arXiv:2009.02653 1, 2020 | 171 | 2020 |
| Multi-stage multi-task feature learning P Gong, J Ye, C Zhang The Journal of Machine Learning Research 14 (1), 2979-3010, 2013 | 165 | 2013 |
| Hexagon-based convolutional neural network for supply-demand forecasting of ride-sourcing services J Ke, H Yang, H Zheng, X Chen, Y Jia, P Gong, J Ye IEEE Transactions on Intelligent Transportation Systems 20 (11), 4160-4173, 2018 | 162 | 2018 |
| Efficient multi-task feature learning with calibration P Gong, J Zhou, W Fan, J Ye Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014 | 60 | 2014 |
| Hierarchical interactions model for predicting Mild Cognitive Impairment (MCI) to Alzheimer's Disease (AD) conversion H Li, Y Liu, P Gong, C Zhang, J Ye, ... PloS one 9 (1), e82450, 2014 | 48 | 2014 |
| Efficient Nonnegative Matrix Factorization via projected Newton method P Gong, C Zhang Pattern Recognition 45 (9), 3557-3565, 2012 | 47 | 2012 |
| Linear convergence of variance-reduced stochastic gradient without strong convexity P Gong, J Ye arXiv preprint arXiv:1406.1102, 2014 | 40* | 2014 |
| Big data analytical approaches to the NACC dataset: aiding preclinical trial enrichment M Lin, P Gong, T Yang, J Ye, RL Albin, HH Dodge Alzheimer Disease & Associated Disorders 32 (1), 18-27, 2018 | 37 | 2018 |
| A survey on machine learning from few samples J Lu, P Gong, J Ye, J Zhang, C Zhang Pattern Recognition 139, 109480, 2023 | 31 | 2023 |
| Efficient euclidean projections via piecewise root finding and its application in gradient projection P Gong, K Gai, C Zhang Neurocomputing 74 (17), 2754-2766, 2011 | 31 | 2011 |
| Computational drug discovery with dyadic positive-unlabeled learning Y Liu, S Qiu, P Zhang, P Gong, F Wang, G Xue, J Ye Proceedings of the 2017 SIAM international conference on data mining, 45-53, 2017 | 28 | 2017 |
| Multi-document summarization via group sparse learning R He, J Tang, P Gong, Q Hu, B Wang Information Sciences 349, 12-24, 2016 | 23 | 2016 |
| Robust convex clustering analysis Q Wang, P Gong, S Chang, TS Huang, J Zhou 2016 IEEE 16th International Conference on Data Mining (ICDM), 1263-1268, 2016 | 22 | 2016 |
| A modified orthant-wise limited memory quasi-Newton method with convergence analysis P Gong, J Ye International Conference on Machine Learning, 276-284, 2015 | 18 | 2015 |
| HONOR: Hybrid optimization for non-convex regularized problems P Gong, J Ye Advances in Neural Information Processing Systems 28, 2015 | 18 | 2015 |
Jieping Ye, IEEE Fellow & ACM Distin...Alibaba GroupVerified email at umich.edu
