Adversarial Training Without Input Gradients via Low-Rank Householder Expansions

arXiv:2608.26963 · cs.LG · Submitted 2026-08-27 · Read on arXiv

cs.LG

Submitted: 2026-08-27

Updated: 2026-08-27

Terminology

• Adversarial Training — 48× in this paper · explained in 1 episode
• Adversarial Examples — 41× in this paper · explained in 2 episodes
• Accuracy — 31× in this paper · explained in 1 episode
• Robustness — 18× in this paper · explained in 5 episodes
• Regularization — 14× in this paper · explained in 3 episodes
• International Conference on Learning Representations — 8× in this paper
• Low-Rank Householder Expansion — 7× in this paper
• Adversarial Robustness — 6× in this paper · explained in 3 episodes
• Adam — 5× in this paper · explained in 2 episodes
• Conference on Computer Vision and Pattern Recognition — 3× in this paper
• International Conference on Machine Learning — 3× in this paper
• Adversarial Attacks — 1× in this paper · explained in 1 episode
• Alternation — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Loss Function — 1× in this paper · explained in 2 episodes

Sources

• On Evaluating Adversarial Robustness
• Robust Learning with Jacobian Regularization
• Improved deterministic l2 robustness on CIFAR-10 and CIFAR-100
• The Space of Transferable Adversarial Examples

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