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Private Distribution Learning with Public Data: The View from Sample Compression

Exploring the Limits of Model-Targeted Indiscriminate Data Poisoning Attacks

Robustness Implies Privacy in Statistical Estimation

New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma

Private Estimation with Public Data

A Private and Computationally-Efficient Estimator for Unbounded Gaussians

Improved Rates for Differentially Private Stochastic Convex Optimization with Heavy-Tailed Data

Robust Estimation for Random Graphs

The Price of Tolerance in Distribution Testing

Calibration with Privacy in Peer Review