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cs.LG2023
Investigating the Corruption Robustness of Image Classifiers with Random Lp-norm Corruptions
Georg Siedel, Weijia Shao, Silvia Vock +1
Robustness is a fundamental property of machine learning classifiers required to achieve safety and reliability. In the field of adversarial robustness of image classifiers, robust…
cs.LG2022
Utilizing Class Separation Distance for the Evaluation of Corruption Robustness of Machine Learning Classifiers
Georg Siedel, Silvia Vock, Andrey Morozov +1
Robustness is a fundamental pillar of Machine Learning (ML) classifiers, substantially determining their reliability. Methods for assessing classifier robustness are therefore esse…