Provable tradeoffs in adversarially robust classification

9 Jun 2020Edgar DobribanHamed HassaniDavid HongAlexander Robey

Machine learning methods can be vulnerable to small, adversarially-chosen perturbations of their inputs, prompting much research into theoretical explanations and algorithms toward improving adversarial robustness. Although a rich and insightful literature has developed around these ideas, many foundational open problems remain... (read more)

PDF Abstract


No code implementations yet. Submit your code now


Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper

🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet