A teacher-student distillation method that carries task knowledge through an out-of-distribution dataset evades all tested dataset-ownership verification methods, according to the authors' experiments.
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Evading Data Provenance in Deep Neural Networks
A teacher-student distillation method that carries task knowledge through an out-of-distribution dataset evades all tested dataset-ownership verification methods, according to the authors' experiments.