On the Adversarial Robustness of Decision Trees and a Symmetry Defense
Gradient-boosting decision tree classifiers (GBDTs) are susceptible to adversarial perturbation attacks that change inputs slightly to cause misclassification. GBDTs are customarily used on non-image datasets that lack inherent symmetries, which might be why data symmetry in the context of GBDT clas...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10843676/ |
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