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stat.ML2024
Agnostic Private Density Estimation for GMMs via List Global Stability
Mohammad Afzali, Hassan Ashtiani, Christopher Liaw
We consider the problem of private density estimation for mixtures of unrestricted high dimensional Gaussians in the agnostic setting. We prove the first upper bound on the sample…
stat.ML2024
Mixtures of Gaussians are Privately Learnable with a Polynomial Number of Samples
Mohammad Afzali, Hassan Ashtiani, Christopher Liaw
We study the problem of estimating mixtures of Gaussians under the constraint of differential privacy (DP). Our main result is that …