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)

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