Cost-sensitive Learning

Provably Cost-Sensitive Adversarial Defense via Randomized Smoothing
We study how to certify and train for cost-sensitive robustness using randomized smoothing.
Yuan Xin, Dingfan Chen, Michael Backes, Xiao Zhang
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Cost-Sensitive Robustness against Adversarial Examples
We propose a notion of cost-sensitive robustness for measuring classifier’s performance when adversarial transformations are not equally important, and provide a certified robust training method to optimize for it.
Xiao Zhang, David Evans
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Cost-Sensitive Robustness against Adversarial Examples