Vikrant Singhal

Differentially Private Algorithms for Learning Mixtures of Separated\n Gaussians

2019 · arXiv (Cornell University)

Learning the parameters of Gaussian mixture models is a fundamental and\nwidely studied problem with numerous applications. In this work, we give new\nalgorithms for learning the parameters of a high-dimensional, well separated,\nGaussian mixture model subject to …

Uniformity Testing Under User-Level Local Privacy

2025 · arXiv (Cornell University)

We initiate the study of distribution testing under \emph{user-level} local differential privacy, where each of $n$ users contributes $m$ samples from the unknown underlying distribution. This setting, albeit very natural, is significantly more challenging that …