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Mixture of Robust Experts (MoRE):A Robust Denoising Method towards multiple perturbations

Authors :
Xu, Kaidi
Wang, Chenan
Cheng, Hao
Kailkhura, Bhavya
Lin, Xue
Goldhahn, Ryan
Publication Year :
2021

Abstract

To tackle the susceptibility of deep neural networks to examples, the adversarial training has been proposed which provides a notion of robust through an inner maximization problem presenting the first-order embedded within the outer minimization of the training loss. To generalize the adversarial robustness over different perturbation types, the adversarial training method has been augmented with the improved inner maximization presenting a union of multiple perturbations e.g., various $\ell_p$ norm-bounded perturbations.<br />Comment: This paper is a seminar and dicussing paper, which will not be published and printed anywhere. And it will be keep updating

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2104.10586
Document Type :
Working Paper