Author:
Pan Yuchen,Xue Yulin,Li Jun,Xu Jianhua
Publisher
Springer Nature Singapore
Reference24 articles.
1. Balasubramanian, K., Lebanon, G.: The landmark selection method for multiple output prediction. In: The 29th International Conference on Machine Learning, pp. 283–290 (2012)
2. Barezi, E.J., Wood, I.D., Fung, P., Rabiee, H.R.: A submodular feature-aware framework for label subset selection in extreme classification problems. In: The 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 1009–1018 (2019)
3. Bi, W., Kwok, J.: Efficient multi-label classification with many labels. In: The 30th International Conference on Machine Learning, pp. 405–413 (2013)
4. Cabral, R., De la Torre, F., Costeira, J.P., Bernardino, A.: Matrix completion for weakly-supervised multi-label image classification. IEEE Trans. Pattern Anal. Mach. Intell. 37(1), 121–135 (2014)
5. Charte, F., Rivera, A.J., Del Jesus, M.J.: Multilabel Classification: Problem Analysis, Metrics and Techniques. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-41111-8