Defending Against Universal Attack Via Curvature-Aware Category Adversarial Training-Reference-Cited by-同舟云学术

Defending Against Universal Attack Via Curvature-Aware Category Adversarial Training

Published:2022-05-23 Issue: Volume: Page:
ISSN:
Container-title:ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Du Peilun¹,Zheng Xiaolong¹,Liu Liang¹,Ma Huadong¹

Affiliation:

1. Beijing University of Posts and Telecommunications,Beijing Key Lab of Intelligent Telecommunication Software and Multimedia,Beijing,China,100876

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9745891/9746004/09746983.pdf?arnumber=9746983

Reference24 articles.

1. Defending Against Universal Attacks Through Selective Feature Regeneration

2. Towards deep learning models resistant to adversarial attacks;madry,2017

3. Adversarial training for free!;shafahi;Advances in neural information processing systems,2019

4. Fast is better than free: Revisiting adversarial training;wong,2020

5. Defense against adversarial attacks using feature scattering-based adversarial training;zhang;Advances in neural information processing systems,2019

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