Efficient and Robust Classification for Sparse Attacks

Author:

Beliaev Mark1,Delgosha Payam2,Hassani Hamed3,Pedarsani Ramtin1

Affiliation:

1. Uni. of California Santa Barbara

2. Uni. of Illinois at Urbana-Champaign

3. Uni. of Pennsylvania

Publisher

IEEE

Reference42 articles.

1. Cifar-10 (canadian institute for advanced research);krizhevsky,0

2. Is bert really robust? natural language attack on text classification and entailment;jin,2019

3. Adversarial perturbations against deep neural networks for malware classification;grosse,2016

4. Adversarial camera stickers: A physical camera-based attack on deep learning systems;li;International Conference on Machine Learning,2019

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Binary Classification Under ℓ0 Attacks for General Noise Distribution;IEEE Transactions on Information Theory;2024-02

2. Efficient and Robust Classification for Sparse Attacks;IEEE Journal on Selected Areas in Information Theory;2024

3. Generalization Properties of Adversarial Training for -ℓ0 Bounded Adversarial Attacks;2023 IEEE Information Theory Workshop (ITW);2023-04-23

4. Efficient and Robust Classification for Sparse Attacks;2022 IEEE International Symposium on Information Theory (ISIT);2022-06-26

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