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Found 2 papers, 2 papers with code
Eliminating Catastrophic Overfitting Via Abnormal Adversarial Examples Regularization
Specifically, we design a novel method, termed Abnormal Adversarial Examples Regularization (AAER), which explicitly regularizes the variation of AAEs to hinder the classifier from becoming distorted.
On the Over-Memorization During Natural, Robust and Catastrophic Overfitting
In this work, we adopt a unified perspective by solely focusing on natural patterns to explore different types of overfitting.
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