Xiao Zhang, David Evans. Cost-Sensitive Robustness against Adversarial Examples. CoRR abs/1810.09225 (2018).

Thang and Evanse propose cost-sensitive certified robustness where different adversarial examples can be weighted based on their actual impact for the application. Specifically, they consider the certified robustness formulation (and the corresponding training scheme) by Wong and Kolter. This formulation is extended by acknowledging that different adversarial examples have different impact for specific applications; this is formulized through a cost matrix which quantifies which source-target label combinations of adversarial examples are actually harmful. Based on this cost matrix, cost-sensitive certified robustness as well as the corresponding training scheme is proposed and evaluated in experiments.

Also find this summary on ShortScience.org.

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