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AdvFunMatch: When Consistent Teaching Meets Adversarial Robustness
To tackle this problem, we propose a simple but effective strategy called Adversarial Function Matching (AdvFunMatch), which aims to match distributions for all data points within the $\ell_p$-norm ball of the training data, in accordance with consistent teaching.
Lower Difficulty and Better Robustness: A Bregman Divergence Perspective for Adversarial Training
In addition, we discuss the function of entropy in TRADES, and we find that models with high entropy can be better robustness learners.
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