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Register a new userA Closer Look at the Adversarial Robustness of Information Bottleneck Models
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Added by
Iryna Korshunova
Publication date
2021
fields
Informatics Engineering
and research's language is
English
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We study the adversarial robustness of information bottleneck models for classification. Previous works showed that the robustness of models trained with information bottlenecks can improve upon adversarial training. Our evaluation under a diverse range of white-box $l_{infty}$ attacks suggests that information bottlenecks alone are not a strong defense strategy, and that previous results were likely influenced by gradient obfuscation.
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