A DUI framework that uses synthetic non-members and mixture proportion estimation to quantify dataset usage in trained models without requiring shadow models or real held-out data.
Open-sourced dataset protection via backdoor watermarking.arXiv preprint arXiv:2010.05821, 2020
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Dataset Usage Inference without Shadow Models or Held-out Data
A DUI framework that uses synthetic non-members and mixture proportion estimation to quantify dataset usage in trained models without requiring shadow models or real held-out data.