Label Correlation Guided Feature Selection for Multi-label Learning
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-46674-8_27
Reference22 articles.
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2. Chen, L., et al.: Predicting gene phenotype by multi-label multi-class model based on essential functional features. Mol. Genet. Genom. 296(4), 905–918 (2021)
3. Chen, Y., Zou, C., Chen, J.: Label-aware graph representation learning for multi-label image classification. Neurocomputing 492, 50–61 (2022)
4. Chen, Z.M., Wei, X.S., Wang, P., Guo, Y.: Multi-label image recognition with graph convolutional networks. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 5177–5186 (2019)
5. Chou, H.C., Lee, C.C., Busso, C.: Exploiting co-occurrence frequency of emotions in perceptual evaluations to train a speech emotion classifier. In: Proceedings of Interspeech, vol. 2022, pp. 161–165 (2022)
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