| Label propagation via teaching-to-learn and learning-to-teach C Gong, D Tao, W Liu, L Liu, J Yang IEEE transactions on neural networks and learning systems 28 (6), 1452-1465, 2016 | 131 | 2016 |
| Airplane detection based on rotation invariant and sparse coding in remote sensing images L Liu, Z Shi Optik 125 (18), 5327-5333, 2014 | 44 | 2014 |
| GoDec+: Fast and robust low-rank matrix decomposition based on maximum correntropy K Guo, L Liu, X Xu, D Xu, D Tao IEEE transactions on neural networks and learning systems 29 (6), 2323-2336, 2017 | 36 | 2017 |
| Toward trainability of quantum neural networks K Zhang, MH Hsieh, L Liu, D Tao arXiv preprint arXiv:2011.06258, 2020 | 35 | 2020 |
| Airport detection based on line segment detector Z Kou, Z Shi, L Liu 2012 International Conference on Computer Vision in Remote Sensing, 72-77, 2012 | 30 | 2012 |
| Deep streaming label learning Z Wang, L Liu, D Tao International Conference on Machine Learning, 9963-9972, 2020 | 23 | 2020 |
| Stochastic zeroth-order optimization via variance reduction method L Liu, M Cheng, CJ Hsieh, D Tao arXiv preprint arXiv:1805.11811, 2018 | 19 | 2018 |
| Diversified dictionaries for multi-instance learning M Qiao, L Liu, J Yu, C Xu, D Tao Pattern Recognition 64, 407-416, 2017 | 19 | 2017 |
| Contrastive graph poisson networks: Semi-supervised learning with extremely limited labels S Wan, Y Zhan, L Liu, B Yu, S Pan, C Gong Advances in Neural Information Processing Systems 34, 6316-6327, 2021 | 18 | 2021 |
| Variance reduced methods for non-convex composition optimization L Liu, J Liu, D Tao IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (9), 5813-5825, 2021 | 18* | 2021 |
| Dualityfree methods for stochastic composition optimization L Liu, J Liu, D Tao IEEE transactions on neural networks and learning systems 30 (4), 1205-1217, 2018 | 12 | 2018 |
| Adaptive curriculum learning Y Kong, L Liu, J Wang, D Tao Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 11 | 2021 |
| Stochastic second-order methods for non-convex optimization with inexact Hessian and gradient L Liu, X Liu, CJ Hsieh, D Tao arXiv preprint arXiv:1809.09853, 2018 | 11 | 2018 |
| Resistance training using prior bias: toward unbiased scene graph generation C Chen, Y Zhan, B Yu, L Liu, Y Luo, B Du Proceedings of the AAAI Conference on Artificial Intelligence 36 (1), 212-220, 2022 | 9 | 2022 |
| Gaussian initializations help deep variational quantum circuits escape from the barren plateau K Zhang, MH Hsieh, L Liu, D Tao arXiv preprint arXiv:2203.09376, 2022 | 9 | 2022 |
| Continual learning through retrieval and imagination Z Wang, L Liu, Y Duan, D Tao Proceedings of the AAAI Conference on Artificial Intelligence 36 (8), 8594-8602, 2022 | 6 | 2022 |
| Toward trainability of deep quantum neural networks K Zhang, MH Hsieh, L Liu, D Tao arXiv preprint arXiv:2112.15002, 2021 | 6 | 2021 |
| Skipnode: On alleviating over-smoothing for deep graph convolutional networks W Lu, Y Zhan, Z Guan, L Liu, B Yu, W Zhao, Y Yang, D Tao arXiv preprint arXiv:2112.11628, 2021 | 6 | 2021 |
| Continual learning with lifelong vision transformer Z Wang, L Liu, Y Duan, Y Kong, D Tao Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 5 | 2022 |
| Quantum Gram-Schmidt processes and their application to efficient state readout for quantum algorithms K Zhang, MH Hsieh, L Liu, D Tao Physical Review Research 3 (4), 043095, 2021 | 5 | 2021 |
