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08/11/2023
Private Distribution Learning with Public Data: The View from Sample Compression
We study the problem of private distribution learning with access to pub...
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04/13/2023
A Polynomial Time, Pure Differentially Private Estimator for Binary Product Distributions
We present the first ε-differentially private, computationally efficient...
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01/30/2023
A Bias-Variance-Privacy Trilemma for Statistical Estimation
The canonical algorithm for differentially private mean estimation is to...
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08/16/2022
Private Estimation with Public Data
We initiate the study of differentially private (DP) estimation with acc...
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05/17/2022
New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma
We prove new lower bounds for statistical estimation tasks under the con...
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11/08/2021
A Private and Computationally-Efficient Estimator for Unbounded Gaussians
We give the first polynomial-time, polynomial-sample, differentially pri...
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05/28/2021
Privately Learning Subspaces
Private data analysis suffers a costly curse of dimensionality. However,...
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02/21/2020
Private Mean Estimation of Heavy-Tailed Distributions
We give new upper and lower bounds on the minimax sample complexity of d...
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09/09/2019
Differentially Private Algorithms for Learning Mixtures of Separated Gaussians
Learning the parameters of a Gaussian mixtures models is a fundamental a...
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05/01/2018
