| When ensemble learning meets deep learning: a new deep support vector machine for classification Z Qi, B Wang, Y Tian, P Zhang Knowledge-Based Systems 107, 54-60, 2016 | 80 | 2016 |
| Search engine marketing, financing ability and firm performance in E-commerce Z Yang, Y Shi, B Wang Procedia Computer Science 55, 1106-1112, 2015 | 78 | 2015 |
| Website quality and profitability evaluation in ecommerce firms using two-stage DEA model ZF Yang, Y Shi, B Wang, H Yan Procedia Computer Science 30, 4-13, 2014 | 50 | 2014 |
| s-lwsr: Super lightweight super-resolution network B Li, B Wang, J Liu, Z Qi, Y Shi IEEE Transactions on Image Processing 29, 8368-8380, 2020 | 41 | 2020 |
| A new application of the support vector regression on the construction of financial conditions index to CPI prediction Y Wang, B Wang, X Zhang Procedia Computer Science 9, 1263-1272, 2012 | 41 | 2012 |
| Learning from Label Proportions with Generative Adversarial Networks J Liu, B Wang, Z Qi, Y Tian, Y Shi Advances in Neural Information Processing Systems, 7169-7179, 2019 | 35 | 2019 |
| Learning with label proportions via NPSVM Z Qi, B Wang, F Meng, L Niu IEEE transactions on cybernetics 47 (10), 3293-3305, 2016 | 35 | 2016 |
| Advertisement click-through rate prediction using multiple criteria linear programming regression model F Wang, W Suphamitmongkol, B Wang Procedia Computer Science 17, 803-811, 2013 | 35 | 2013 |
| Fast and accurate road crack detection based on adaptive cost-sensitive loss function K Li, B Wang, Y Tian, Z Qi IEEE Transactions on Cybernetics 53 (2), 1051-1062, 2021 | 32 | 2021 |
| Learning with label proportions based on nonparallel support vector machines Z Chen, Z Qi, B Wang, L Cui, F Meng, Y Shi Knowledge-Based Systems 119, 126-141, 2017 | 31 | 2017 |
| Learning from label proportions on high-dimensional data Y Shi, J Liu, Z Qi, B Wang Neural Networks 103, 9-18, 2018 | 24 | 2018 |
| Bi-directional pyramid network for edge detection K Li, Y Tian, B Wang, Z Qi, Q Wang Electronics 10 (3), 329, 2021 | 22 | 2021 |
| Linear twin svm for learning from label proportions B Wang, Z Chen, Z Qi 2015 IEEE/WIC/ACM International Conference on Web Intelligence and …, 2015 | 19 | 2015 |
| Deep learning from label proportions with labeled samples Y Shi, J Liu, B Wang, Z Qi, YJ Tian Neural Networks 128, 73-81, 2020 | 17 | 2020 |
| Two-stage training for learning from label proportions J Liu, B Wang, X Shen, Z Qi, Y Tian arXiv preprint arXiv:2105.10635, 2021 | 16 | 2021 |
| SELF-LLP: Self-supervised learning from label proportions with self-ensemble J Liu, Z Qi, B Wang, YJ Tian, Y Shi Pattern Recognition 129, 108767, 2022 | 11 | 2022 |
| World search engine IQ test based on the internet IQ evaluation algorithms F Liu, Y Shi, B Wang International Journal of Information Technology & Decision Making 14 (02 …, 2015 | 11 | 2015 |
| Error correction method in classification by using multiple-criteria and multiple-constraint levels linear programming B Wang, Y Shi International Journal of Computers Communications & Control 7 (5), 976-989, 2012 | 10 | 2012 |
| Unsupervised single-image super-resolution with multi-gram loss Y Shi, B Li, B Wang, Z Qi, J Liu Electronics 8 (8), 833, 2019 | 9 | 2019 |
| Semi-supervised classification with privileged information Z Qi, Y Tian, L Niu, B Wang International Journal of Machine Learning and Cybernetics 6, 667-676, 2015 | 9 | 2015 |
zhiquan qi, 齐志泉University of Chinese Academy of SciencesVerified email at ucas.ac.cn
