| AdvSGAN: Adversarial image Steganography with adversarial networks L Li, M Fan, D Liu Multimedia Tools and Applications 80 (17), 25539-25555, 2021 | 15 | 2021 |
| Robust binary loss for multi-category classification with label noise D Liu, G Yang, J Wu, J Zhao, F Lv ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 8 | 2021 |
| Multi-category Classification with Label Noise by Robust Binary Loss D Liu, J Zhao, J Wu, G Yang, F Lv Neurocomputing, 2022 | 6 | 2022 |
| Extending ordinary-label learning losses to complementary-label learning D Liu, J Ning, J Wu, G Yang IEEE Signal Processing Letters 28, 852-856, 2021 | 5 | 2021 |
| Quantization-based hashing with optimal bits for efficient recommendation Y Zhang, D Liu, G Yang, L Hu Multimedia Tools and Applications 79, 33907-33924, 2020 | 4 | 2020 |
| A convergence path to deep learning on noisy labels D Liu, IW Tsang, G Yang IEEE Transactions on Neural Networks and Learning Systems, 2022 | 3 | 2022 |
| Gradient boosting tree for 1H-MRS Alzheimer diagnosis D Liu, G Yang, Y Li, J Wu, F Lv International Journal of Data Mining and Bioinformatics 23 (1), 12-29, 2020 | 2 | 2020 |
| Noisy Label Learning With Provable Consistency for a Wider Family of Losses D Liu, W Li, L Duan, IW Tsang, G Yang IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 | 1 | 2023 |
| Semi-supervised learning for breast-ultrasound image M Zhang, G Yang, D Liu, J Wu 2nd International Conference on Artificial Intelligence, Automation, and …, 2022 | 1 | 2022 |
| Simple and effective complementary label learning based on mean square error loss C Wang, X Xu, D Liu, X Niu, S Han Machine Vision and Applications 34 (6), 118, 2023 | | 2023 |
| Partial multi-label learning with cross-validation L Kong, G Yang, D Liu, J Wu 2nd International Conference on Artificial Intelligence, Automation, and …, 2022 | | 2022 |
