| Robust low-rank tensor recovery with rectification and alignment X Zhang, D Wang, Z Zhou, Y Ma IEEE Transactions on Pattern Analysis and Machine Intelligence 43 (1), 238-255, 2019 | 184 | 2019 |
| Top-k Feature Selection Framework Using Robust 0–1 Integer Programming X Zhang, M Fan, D Wang, P Zhou, D Tao IEEE Transactions on Neural Networks and Learning Systems 32 (7), 3005-3019, 2020 | 131 | 2020 |
| An explicit nonlinear mapping for manifold learning H Qiao, P Zhang, D Wang, B Zhang IEEE transactions on cybernetics 43 (1), 51-63, 2012 | 105 | 2012 |
| Online support vector machine based on convex hull vertices selection D Wang, H Qiao, B Zhang, M Wang IEEE transactions on neural networks and learning systems 24 (4), 593-609, 2013 | 90 | 2013 |
| Exemplar-based denoising: A unified low-rank recovery framework X Zhang, J Zheng, D Wang, L Zhao IEEE Transactions on Circuits and Systems for Video Technology 30 (8), 2538-2549, 2019 | 48 | 2019 |
| Simultaneous rectification and alignment via robust recovery of low-rank tensors X Zhang, D Wang, Z Zhou, Y Ma Advances in Neural Information Processing Systems 26, 2013 | 39 | 2013 |
| Distributed kernel ridge regression with communications SB Lin, D Wang, DX Zhou Journal of Machine Learning Research 21 (93), 1-38, 2020 | 34 | 2020 |
| Semi-supervised dictionary learning via structural sparse preserving D Wang, X Zhang, M Fan, X Ye Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016 | 34 | 2016 |
| An online core vector machine with adaptive MEB adjustment D Wang, B Zhang, P Zhang, H Qiao Pattern Recognition 43 (10), 3468-3482, 2010 | 32 | 2010 |
| Hybrid singular value thresholding for tensor completion X Zhang, Z Zhou, D Wang, Y Ma Proceedings of the AAAI Conference on Artificial Intelligence 28 (1), 2014 | 26 | 2014 |
| Self-taught semisupervised dictionary learning with nonnegative constraint X Zhang, Q Liu, D Wang, L Zhao, N Gu, S Maybank IEEE Transactions on Industrial Informatics 16 (1), 532-543, 2019 | 25 | 2019 |
| Top-k Supervise Feature Selection via ADMM for Integer Programming. M Fan, X Chang, X Zhang, Di Wang 0008, L Du IJCAI, 1646-1653, 2017 | 23 | 2017 |
| Hierarchical mixing linear support vector machines for nonlinear classification D Wang, X Zhang, M Fan, X Ye Pattern Recognition 59, 255-267, 2016 | 23 | 2016 |
| Random sketching for neural networks with ReLU D Wang, J Zeng, SB Lin IEEE Transactions on Neural Networks and Learning Systems 32 (2), 748-762, 2020 | 21 | 2020 |
| Structured Sparsity Optimization With Non-Convex Surrogates of -Norm: A Unified Algorithmic Framework X Zhang, J Zheng, D Wang, G Tang, Z Zhou, Z Lin IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (5), 6386-6402, 2022 | 18 | 2022 |
| A kernel-based sparsity preserving method for semi-supervised classification N Gu, D Wang, M Fan, D Meng Neurocomputing 139, 345-356, 2014 | 18 | 2014 |
| Multi-view subspace clustering based on tensor schatten-p norm Y Liu, X Zhang, G Tang, D Wang 2019 IEEE international conference on big data (big data), 5048-5055, 2019 | 15 | 2019 |
| Manifold based fisher method for semi-supervised feature selection S Lv, H Jiang, L Zhao, D Wang, M Fan 2013 10th International Conference on Fuzzy Systems and Knowledge Discovery …, 2013 | 14 | 2013 |
| Convergence of decomposition methods for support vector machines Q Zhang, D Wang, Y Wang Neurocomputing 317, 179-187, 2018 | 11 | 2018 |
| Structure regularized self-paced learning for robust semi-supervised pattern classification N Gu, P Fan, M Fan, D Wang Neural Computing and Applications 31, 6559-6574, 2019 | 4 | 2019 |
