Methods › General › Adversarial Attacks › Fast Minimum-Norm Attack
Fast Minimum-Norm Attack
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Fast Minimum-Norm Attack, or FNM, is a type of adversarial attack that works with different ℓₚ-norm perturbation models (p=0,1,2,∞), is robust to hyperparameter choices, does not require adversarial starting points, and converges within few lightweight steps. It works by iteratively finding the sample misclassified with maximum confidence within an ℓₚ-norm constraint of size ϵ, while adapting ϵ to minimize the distance of the current sample to the decision boundary.
Papers archive 2025-07-28
2 shown of 2, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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HO-FMN: Hyperparameter Optimization for Fast Minimum-Norm Attacks 11 Jul 2024 · 1 repository · arXiv:2407.08806
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Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints 25 Feb 2021 · 3 repositories · arXiv:2102.12827Syntology ran 2 of 2 samples · 0 unverified
Tasks archive 2025-07-28
3 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
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