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Research map / Adversarial robustness and security / Certified and empirical robustness

Towards Consistency in Adversarial Classification

NeurIPS 2022 · Adversarial robustness and security › Certified and empirical robustness · approach: Attack evaluation and defense critique · 3 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
use a convex margin surrogate at positive adversarial radiusadversarial classification · adversarial classificationadversarial calibrationHurt
shift an odd margin loss by a positive offsetodd margin losses · adversarial classificationadversarial calibrationHelped
use a standard-calibrated margin loss on an ε-realisable distributionadversarial classification · ε-realisable distributionsadversarial consistencyHelped
use a 0/1-like margin lossadversarial classification · distributions on spaces with the midpoint propertyoptimal adversarial riskNo clear effect

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