Toward robustness in multi-label classification: A data augmentation strategy against imbalance and noise

H Song, M Kim, JG Lee - Proceedings of the AAAI Conference on …, 2024 - ojs.aaai.org
Multi-label classification poses challenges due to imbalanced and noisy labels in training
data. In this paper, we propose a unified data augmentation method, named BalanceMix, to …
被引用次数：4 相关文章

Toward Robustness in Multi-label Classification: A Data Augmentation Strategy against Imbalance and Noise

H Song, M Kim, JG Lee - arXiv preprint arXiv:2312.07087, 2023 - arxiv.org
Multi-label classification poses challenges due to imbalanced and noisy labels in training
data. We propose a unified data augmentation method, named BalanceMix, to address …

Toward Robustness in Multi-label Classification: A Data Augmentation Strategy against Imbalance and Noise

H Song, M Kim, JG Lee - arXiv e-prints, 2023 - ui.adsabs.harvard.edu
Multi-label classification poses challenges due to imbalanced and noisy labels in training
data. We propose a unified data augmentation method, named BalanceMix, to address …