Meta-weight-net: Learning an explicit mapping for sample weighting J Shu, Q Xie, L Yi, Q Zhao, S Zhou, Z Xu, D Meng NeurIPS, 2019 | 103 | 2019 |
Small sample learning in big data era J Shu, Z Xu, D Meng arXiv preprint arXiv:1808.04572, 2018 | 36 | 2018 |
Learning adaptive loss for robust learning with noisy labels J Shu, Q Zhao, K Chen, Z Xu, D Meng arXiv preprint arXiv:2002.06482, 2020 | 8 | 2020 |
Multi-view based integrative analysis of gene expression data for identifying biomarkers ZY Yang, XY Liu, J Shu, H Zhang, YQ Ren, ZB Xu, Y Liang Scientific reports 9 (1), 1-15, 2019 | 6 | 2019 |
Meta Transition Adaptation for Robust Deep Learning with Noisy Labels J Shu, Q Zhao, Z Xu, D Meng arXiv preprint arXiv:2006.05697, 2020 | 3 | 2020 |
Variational label enhancement N Xu, J Shu, YP Liu, X Geng International Conference on Machine Learning, 10597-10606, 2020 | 1 | 2020 |
Meta Feature Modulator for Long-tailed Recognition R Wang, K Hu, Y Zhu, J Shu, Q Zhao, D Meng arXiv preprint arXiv:2008.03428, 2020 | 1 | 2020 |
Meta self-paced learning J SHU, D MENG, Z XU SCIENTIA SINICA Informationis 50 (6), 781-793, 2020 | 1 | 2020 |
Select-ProtoNet: Learning to Select for Few-Shot Disease Subtype Prediction Z Yang, J Shu, Y Liang, D Meng, Z Xu arXiv preprint arXiv:2009.00792, 2020 | | 2020 |
Learning to Purify Noisy Labels via Meta Soft Label Corrector Y Wu, J Shu, Q Xie, Q Zhao, D Meng arXiv preprint arXiv:2008.00627, 2020 | | 2020 |
Meta-LR-Schedule-Net: Learned LR Schedules that Scale and Generalize J Shu, Y Zhu, Q Zhao, D Meng, Z Xu arXiv preprint arXiv:2007.14546, 2020 | | 2020 |