Publisher
Springer Science and Business Media LLC
Reference36 articles.
1. Z. D. Ge, S. Mahapatra, S. Sedai, R. Garnavi, R. Chakravorty. Chest X-rays classification: A multi-label and finegrained problem, [Online], Available: https://arxiv.org/abs/1807.07247, 2018.
2. M. K. Xie, S. J. Huang. Partial multi-label learning. In Proceedings of the 32nd AAAI Conference on Artificial Intelligence, Louisiana, USA, pp. 4302–4309, 2018. DOI: https://doi.org/10.1609/aaai.v32i1.11644.
3. L. J. Sun, S. H. Feng, T. Wang, C. Y. Lang, Y. Jin. Partial multi-label learning by low-rank and sparse decomposition. In Proceedings of the 33rd AAAI Conference on Artificial Intelligence, Honolulu, USA, pp. 5016–5023, 2019. DOI: https://doi.org/10.1609/aaai.v33i01.33015016.
4. M. L. Zhang, J. P. Fang. Partial multi-label learning via credible label elicitation. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 43, no. 10, pp. 3587–3599, 2021. DOI: https://doi.org/10.1109/TPAMI.2020.2985210.
5. H. B. Wang, W. W. Liu, Y. Zhao, C. Zhang, T. L. Hu, G. Chen. Discriminative and correlative partial multi-label learning. In Proceedings of the 28th International Joint Conference on Artificial Intelligence, Macao, China, pp. 3691–3697, 2019.