Methods › General › Adversarial Attacks › Fast Minimum-Norm Attack

Fast Minimum-Norm Attack

2 papers tagged archive 2025-07-28

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.

Source: Fast Minimum-norm Adversarial Attacks through Adaptive...

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.

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.

TaskPapers
Adversarial Robustness2
Adversarial Attack1
Hyperparameter Optimization1

Usage over time archive 2025-07-28

Papers per year tagged with Fast Minimum-Norm Attack: 2021 to 2024, peak 1 1 0 2021: 1 paper 2021 2022: 0 papers 2022 2023: 0 papers 2023 2024: 1 paper 2024
Papers per year the archive tags with this method, by the paper's archive date (2 dated). Bars are counts, not a trend claim.

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

Adversarial Attacks

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections