A hypothesis testing approach to distributional unlearning that characterizes allowable edited distributions and removal-preservation Pareto frontiers for parametric and nonparametric families including Gaussians, Poisson, and Gaussian white noise.
[2026]: the unlearning framework Proposition 1(Comparison with (α, ε) unlearning Allouah et al
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Statistical Unlearning of Distributions: A Hypothesis Testing Approach
A hypothesis testing approach to distributional unlearning that characterizes allowable edited distributions and removal-preservation Pareto frontiers for parametric and nonparametric families including Gaussians, Poisson, and Gaussian white noise.