Cost-Sensitive Robustness against Adversarial Examples Cost-Sensitive Robustness against Adversarial Examples
Paper summary 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 at [](
Cost-Sensitive Robustness against Adversarial Examples
Zhang, Xiao and Evans, David
arXiv e-Print archive - 2018 via Local Bibsonomy
Keywords: dblp

Summary by David Stutz 1 year ago
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