Revealing Perceptible Backdoors in DNNs, Without the Training Set, via the Maximum Achievable Misclassification Fraction Statistic

Research article (2020 IEEE 30th International Workshop on Machine Learning for Signal Processing (MLSP), 2020) · cited 10× · AI/ML
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Revealing Perceptible Backdoors in DNNs, Without the Training Set, via the Maximum Achievable Misclassification Fraction Statistic

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APA 4ort.xyz Knowledge Graph. (2026). Revealing Perceptible Backdoors in DNNs, Without the Training Set, via the Maximum Achievable Misclassification Fraction Statistic. Retrieved May 24, 2026, from https://4ort.xyz/entity/revealing-perceptible-backdoors-in-dnns-without-the-training-set-via-the-maximum-achievable-misclassification-fraction-s
MLA “Revealing Perceptible Backdoors in DNNs, Without the Training Set, via the Maximum Achievable Misclassification Fraction Statistic.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/revealing-perceptible-backdoors-in-dnns-without-the-training-set-via-the-maximum-achievable-misclassification-fraction-s.
BibTeX @misc{4ortxyz_revealing-perceptible-backdoors-in-dnns-without-the-training-set-via-the-maximum-achievable-misclassification-fraction-s_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Revealing Perceptible Backdoors in DNNs, Without the Training Set, via the Maximum Achievable Misclassification Fraction Statistic}}, year = {2026}, url = {https://4ort.xyz/entity/revealing-perceptible-backdoors-in-dnns-without-the-training-set-via-the-maximum-achievable-misclassification-fraction-s}, note = {Accessed: 2026-05-24}}
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