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stat.ML2026
Differentially Private Sampling from Distributions via Wasserstein Projection
Shokichi Takakura, Seng Pei Liew, Satoshi Hasegawa
In this paper, we study the problem of sampling from a distribution under the constraint of differential privacy (DP). Prior works measure the utility of DP sampling with density r…
stat.ML2025
Optimal Variance and Covariance Estimation under Differential Privacy in the Add-Remove Model and Beyond
Shokichi Takakura, Seng Pei Liew, Satoshi Hasegawa
In this paper, we study the problem of estimating the variance and covariance of datasets under differential privacy in the add-remove model. While estimation in the swap model has…