berry-esseen bound 1combinatorial designs 1hypergraph theory 1incomplete u-statistics 1kernel tests 1u-statistics 1
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stat.ML2026
Near-Optimal Private Tests for Simple and MLR Hypotheses
Yu-Wei Chen, Raghu Pasupathy, Jordan Awan
We develop a near-optimal testing procedure under the framework of Gaussian differential privacy for simple as well as one- and two-sided tests under monotone likelihood ratio cond…
stat.ML2026
Beyond Data Splitting: Full-Data Conformal Prediction by Differential Privacy
Young Hyun Cho, Jordan Awan
Privacy protection and uncertainty quantification are increasingly important in data-driven decision making. Conformal prediction provides finite-sample marginal coverage, but exis…
stat.ML2025
Optimal Survey Design for Private Mean Estimation
Yu-Wei Chen, Raghu Pasupathy, Jordan A. Awan
This work identifies the first privacy-aware stratified sampling scheme that minimizes the variance for general private mean estimation under the Laplace, Discrete Laplace (DLap) a…