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cs.LG2026
Risk-Equalized Differentially Private Synthetic Data: Protecting Outliers by Controlling Record-Level Influence
Amir Asiaee, Chao Yan, Zachary B. Abrams +1
When synthetic data is released, some individuals are harder to protect than others. A patient with a rare disease combination or a transaction with unusual characteristics stands…
cs.LG2026
PRISM: Differentially Private Synthetic Data with Structure-Aware Budget Allocation for Prediction
Amir Asiaee, Chao Yan, Zachary B. Abrams +1
Differential privacy (DP) provides a mathematical guarantee limiting what an adversary can learn about any individual from released data. However, achieving this protection typical…
cs.LG2026
Private Prediction via Shrinkage
Chao Yan
We study differentially private prediction introduced by Dwork and Feldman (COLT 2018): an algorithm receives one labeled sample set and then answers a stream of unlabeled quer…