论文标题

CEB提高模型鲁棒性

CEB Improves Model Robustness

论文作者

Fischer, Ian, Alemi, Alexander A.

论文摘要

我们证明条件熵瓶颈(CEB)可以改善模型鲁棒性。 CEB是一个简单的策略,可以与数据增强程序同时实施和合作。我们报告了对CIFAR-10的大规模对抗性鲁棒性研究的结果,以及Imagenet-C共同损坏基准,Imagenet-A和PGD攻击。

We demonstrate that the Conditional Entropy Bottleneck (CEB) can improve model robustness. CEB is an easy strategy to implement and works in tandem with data augmentation procedures. We report results of a large scale adversarial robustness study on CIFAR-10, as well as the ImageNet-C Common Corruptions Benchmark, ImageNet-A, and PGD attacks.

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