{
  "id": "2002.05380",
  "version": "v1",
  "published": "2020-02-13T07:49:22.000Z",
  "updated": "2020-02-13T07:49:22.000Z",
  "title": "CEB Improves Model Robustness",
  "authors": [
    "Ian Fischer",
    "Alexander A. Alemi"
  ],
  "categories": [
    "cs.LG",
    "stat.ML"
  ],
  "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, ImageNet-A, and PGD attacks.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2020-02-13T07:49:22.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "model robustness",
      "large scale adversarial robustness study",
      "imagenet-c common corruptions benchmark",
      "conditional entropy bottleneck",
      "data augmentation procedures"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}