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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

Efficient Mean Estimation with Pure Differential Privacy via a Sum-of-Squares Exponential Mechanism

Differentially Private Fine-tuning of Language Models

The Role of Adaptive Optimizers for Honest Private Hyperparameter Selection

Don’t Generate Me: Training Differentially Private Generative Models with Sinkhorn Divergence