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Preprint
Mixture of Robust Experts (MoRE):A Robust Denoising Method towards multiple perturbations
arXiv.org
20 Jul 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.
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Details
- Title
- Mixture of Robust Experts (MoRE):A Robust Denoising Method towards multiple perturbations
- Creators
- Kaidi XuChenan WangHao ChengBhavya KailkhuraXue LinRyan Goldhahn
- Publication Details
- arXiv.org
- Resource Type
- Preprint
- Language
- English
- Academic Unit
- Computer Science (Computing)
- Other Identifier
- 991021871342804721