Towards fair class-wise robustness: class optimal distribution adversarial training
Abstract Adversarial training has proven to be a highly effective method for improving the robustness of deep neural networks against adversarial attacks. Nonetheless, it has been observed to exhibit a limitation in terms of robust fairness, characterized by a significant disparity in robustness acr...
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| Autores principales: | , , , , |
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| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
Springer
2025-07-01
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| Colección: | Complex & Intelligent Systems |
| Materias: | |
| Acceso en línea: | https://doi.org/10.1007/s40747-025-02038-w |
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