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Minimax bounds for watermarked and masked recursive discrete distribution estimation

Kanabar, Millen et al.
arXiv (All) · Papers
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information-theorymachine-learningstatistics-theory
Watermarking has been proposed as a way to identify synthetic samples in estimation settings where no metadata is available to distinguish them from real samples, but its precise effects remain unexplored. In the absence of a distinguishing mechanism, it has been shown that adding synthetic samples
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