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stat.ML2026
Private Evaluation of High-Dimensional Functions
Mohammad Afzali, Hassan Ashtiani, Adam Smith
We study differentially private black-box evaluation of arbitrary high-dimensional functions. Given a dataset and query access to a function ---whose sensitivity may be unkn…
stat.ML2026
Efficient Agnostic Learning of Univariate Densities Under Local Differential Privacy
Mohammad Afzali, Hassan Ashtiani, Sivan Sabato
We propose a general framework for non-interactive locally differentially private (LDP) learning of structured univariate distributions that can be approximated by piece-wise polyn…