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A Bias-Variance-Privacy Trilemma for Statistical Estimation

Rethinking Benchmarks for Differentially Private Image Classification

Unbiased Statistical Estimation and Valid Confidence Intervals Under Differential Privacy

The Broader Landscape of Robustness in Algorithmic Statistics

Differentially Private Fine-tuning of Language Models

Advancing Differential Privacy: Where We Are Now and Future Directions for Real-World Deployment

Individual Privacy Accounting for Differentially Private Stochastic Gradient Descent

Private GANs, Revisited

Indiscriminate Data Poisoning Attacks on Neural Networks

The Discrete Gaussian for Differential Privacy