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Adversarial Robustness for Tabular Data through Cost and Utility Awareness. (arXiv:2208.13058v1 [cs.LG])
Aug. 30, 2022, 1:20 a.m. | Klim Kireev, Bogdan Kulynych, Carmela Troncoso
cs.CR updates on arXiv.org arxiv.org
Many machine learning problems use data in the tabular domains. Adversarial
examples can be especially damaging for these applications. Yet, existing works
on adversarial robustness mainly focus on machine-learning models in the image
and text domains. We argue that due to the differences between tabular data and
images or text, existing threat models are inappropriate for tabular domains.
These models do not capture that cost can be more important than
imperceptibility, nor that the adversary could ascribe different value to …
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