CEB Improves Model RobustnessDownload PDF

25 Sept 2019 (modified: 22 Oct 2023)ICLR 2020 Conference Blind SubmissionReaders: Everyone
Keywords: Information Theory, Adversarial Robustness
TL;DR: Training your model with the Conditional Entropy Bottleneck is easy and makes your model more robust.
Abstract: 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.
Community Implementations: [![CatalyzeX](/images/catalyzex_icon.svg) 1 code implementation](https://www.catalyzex.com/paper/arxiv:2002.05380/code)
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