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Adversarial robustness assessment: Why in evaluation both L(0) and L(∞) attacks are necessary
There are different types of adversarial attacks and defences for machine learning algorithms which makes assessing the robustness of an algorithm a daunting task. Moreover, there is an intrinsic bias in these adversarial attacks and defences to make matters worse. Here, we organise the problems fac...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Public Library of Science
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9009601/ https://www.ncbi.nlm.nih.gov/pubmed/35421125 http://dx.doi.org/10.1371/journal.pone.0265723 |