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Description of the model/defense: We use the curriculum learning framework to schedule the "difficulty" of adversarial examples generated during adversarial training. This improves both clean and robust accuracy.
The text was updated successfully, but these errors were encountered:
Paper: Improving Adversarial Robustness Through Progressive Hardening https://arxiv.org/abs/2003.09347
Venue: under review
Dataset and threat model: CIFAR-10, L-inf, 8/255
Code: https://github.com/chawins/ates-minimal
Pre-trained model: weight
Log file: log
Additional data: no
Clean and robust accuracy: 86.84/50.72
Architecture: WRN-34-10
Description of the model/defense: We use the curriculum learning framework to schedule the "difficulty" of adversarial examples generated during adversarial training. This improves both clean and robust accuracy.
The text was updated successfully, but these errors were encountered: