Adversarial consistency and the uniqueness of the adversarial bayes classifier
Minimizing an adversarial surrogate risk is a common technique for learning robust classifiers. Prior work showed that convex surrogate losses are not statistically consistent in the adversarial context – or in other words, a minimizing sequence of the adversarial surrogate risk will not necessarily...
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| Main Author: | Natalie S. Frank |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Cambridge University Press
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| Series: | European Journal of Applied Mathematics |
| Subjects: | |
| Online Access: | https://www.cambridge.org/core/product/identifier/S0956792525000038/type/journal_article |
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