| 3D convolutional neural networks for human action recognition S Ji, W Xu, M Yang, K Yu IEEE Transactions on Pattern Analysis and Machine Intelligence 35 (1), 221-231, 2013 | 3404 | 2013 |
| SLEP: Sparse learning with efficient projections J Liu, S Ji, J Ye Arizona State University 6 (491), 7, 2009 | 666* | 2009 |
| Multi-task feature learning via efficient l2, 1-norm minimization J Liu, S Ji, J Ye arXiv preprint arXiv:1205.2631, 2012 | 597 | 2012 |
| An accelerated gradient method for trace norm minimization S Ji, J Ye Proceedings of the 26th annual international conference on machine learning …, 2009 | 480 | 2009 |
| Deep convolutional neural networks for multi-modality isointense infant brain image segmentation W Zhang, R Li, H Deng, L Wang, W Lin, S Ji, D Shen NeuroImage 108, 214-224, 2015 | 477 | 2015 |
| Deep learning based imaging data completion for improved brain disease diagnosis R Li, W Zhang, HI Suk, L Wang, J Li, D Shen, S Ji International Conference on Medical Image Computing and Computer-Assisted …, 2014 | 262 | 2014 |
| Canonical correlation analysis for multilabel classification: A least-squares formulation, extensions, and analysis L Sun, S Ji, J Ye IEEE Transactions on Pattern Analysis and Machine Intelligence 33 (1), 194-200, 2010 | 259 | 2010 |
| Discriminant sparse neighborhood preserving embedding for face recognition J Gui, Z Sun, W Jia, R Hu, Y Lei, S Ji Pattern Recognition 45 (8), 2884-2893, 2012 | 253 | 2012 |
| Hypergraph spectral learning for multi-label classification L Sun, S Ji, J Ye Proceedings of the 14th ACM SIGKDD international conference on Knowledge …, 2008 | 230 | 2008 |
| Extracting shared subspace for multi-label classification S Ji, L Tang, S Yu, J Ye Proceedings of the 14th ACM SIGKDD international conference on Knowledge …, 2008 | 211 | 2008 |
| Trace norm regularization: Reformulations, algorithms, and multi-task learning TK Pong, P Tseng, S Ji, J Ye SIAM Journal on Optimization 20 (6), 3465-3489, 2010 | 163 | 2010 |
| Generalized linear discriminant analysis: a unified framework and efficient model selection S Ji, J Ye IEEE Transactions on Neural Networks 19 (10), 1768-1782, 2008 | 157 | 2008 |
| Feature selection based on structured sparsity: A comprehensive study J Gui, Z Sun, S Ji, D Tao, T Tan IEEE transactions on neural networks and learning systems 28 (7), 1490-1507, 2016 | 153 | 2016 |
| A shared-subspace learning framework for multi-label classification S Ji, L Tang, S Yu, J Ye ACM Transactions on Knowledge Discovery from Data (TKDD) 4 (2), 1-29, 2010 | 152 | 2010 |
| A robust deep model for improved classification of AD/MCI patients F Li, L Tran, KH Thung, S Ji, D Shen, J Li IEEE journal of biomedical and health informatics 19 (5), 1610-1616, 2015 | 130 | 2015 |
| Multi-class discriminant kernel learning via convex programming J Ye, S Ji, J Chen Journal of Machine Learning Research 9 (Apr), 719-758, 2008 | 115 | 2008 |
| Drosophila gene expression pattern annotation through multi-instance multi-label learning YX Li, S Ji, S Kumar, J Ye, ZH Zhou IEEE/ACM Transactions on Computational Biology and Bioinformatics 9 (1), 98-112, 2011 | 108 | 2011 |
| Linear dimensionality reduction for multi-label classification S Ji, J Ye Twenty-first International Joint Conference on Artificial Intelligence, 2009 | 102 | 2009 |
| Deep model based transfer and multi-task learning for biological image analysis W Zhang, R Li, T Zeng, Q Sun, S Kumar, J Ye, S Ji IEEE transactions on Big Data, 2016 | 100 | 2016 |
| Large-scale learnable graph convolutional networks H Gao, Z Wang, S Ji Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018 | 98 | 2018 |
Jieping Ye, IEEE FellowUniversity of Michigan & Didi ChuxingVerified email at umich.edu
