2 papers
cs.LG2024
Sample-Efficient Private Learning of Mixtures of Gaussians
Hassan Ashtiani, Mahbod Majid, Shyam Narayanan
We study the problem of learning mixtures of Gaussians with approximate differential privacy. We prove that roughly samples suffice to learn a mix…
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…