Margin-controlled interpolation between clean and PGD examples, combined with a curriculum-style epsilon schedule, improves both clean accuracy and robust accuracy of semi-supervised adversarial training in low-label regimes.
Are labels required for improving adversarial robustness? Ad- vances in Neural Information Processing Systems, 32, 2019
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Adversarial Training in Low-Label Regimes with Margin-Based Interpolation
Margin-controlled interpolation between clean and PGD examples, combined with a curriculum-style epsilon schedule, improves both clean accuracy and robust accuracy of semi-supervised adversarial training in low-label regimes.