Exposing previously undetectable faults in deep neural networks
Existing methods for testing DNNs solve the oracle problem by constraining the raw features (e.g. image pixel values) to be within a small distance of a dataset example for which the desired DNN output is known. But this limits the kinds of faults these approaches are able to detect. In this paper,...
Principais autores: | , , , |
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Formato: | Conference item |
Idioma: | English |
Publicado em: |
Association for Computing Machinery
2021
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