ECLIPSE: Expunging Clean-Label Indiscriminate Poisons via Sparse Diffusion Purification

Author:

Wang XianlongORCID,Hu ShengshanORCID,Zhang YechaoORCID,Zhou ZiqiORCID,Zhang Leo YuORCID,Xu PengORCID,Wan WeiORCID,Jin HaiORCID

Publisher

Springer Nature Switzerland

Reference49 articles.

1. Biggio, B., Nelson, B., Laskov, P.: Support vector machines under adversarial label noise. In: Proceedings of the 3rd Asian Conference on Machine Learning (ACML’11), pp. 97–112 (2011)

2. Borgnia, E., et al.: Strong data augmentation sanitizes poisoning and backdoor attacks without an accuracy tradeoff. In: Proceedings of the 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP’21), pp. 3855–3859 (2021)

3. Chen, S., et al.: Self-ensemble protection: training checkpoints are good data protectors. In: Proceedings of the 11th International Conference on Learning Representations (ICLR’23) (2023)

4. Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., Li, F.: Imagenet: a large-scale hierarchical image database. In: Proceedings of the 2009 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR’09), pp. 248–255 (2009)

5. DeVries, T., Taylor, G.W.: Improved regularization of convolutional neural networks with cutout. arXiv preprint arXiv:1708.04552 (2017)

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