Awan, Jordan

15 publications

JMLR 2025 Best Linear Unbiased Estimate from Privatized Contingency Tables Jordan Awan, Adam Edwards, Paul Bartholomew, Andrew Sillers

JMLR 2025 Differentially Private Bootstrap: New Privacy Analysis and Inference Strategies Zhanyu Wang, Guang Cheng, Jordan Awan

JMLR 2025 Locally Private Causal Inference for Randomized Experiments Yuki Ohnishi, Jordan Awan

ICML 2025 Optimal Survey Design for Private Mean Estimation Yu-Wei Chen, Raghu Pasupathy, Jordan Awan

JMLR 2024 Differentially Private Topological Data Analysis Taegyu Kang, Sehwan Kim, Jinwon Sohn, Jordan Awan

JMLR 2024 Optimizing Noise for F-Differential Privacy via Anti-Concentration and Stochastic Dominance Jordan Awan, Aishwarya Ramasethu

JMLR 2023 Privacy-Aware Rejection Sampling Jordan Awan, Vinayak Rao

NeurIPS 2022 Data Augmentation MCMC for Bayesian Inference from Privatized Data Nianqiao Ju, Jordan Awan, Ruobin Gong, Vinayak Rao

NeurIPS 2022 Log-Concave and Multivariate Canonical Noise Distributions for Differential Privacy Jordan Awan, Jinshuo Dong

NeurIPSW 2021 Canonical Noise Distributions and Private Hypothesis Tests Jordan Awan, Salil Vadhan

NeurIPSW 2021 Privacy-Aware Rejection Sampling Jordan Awan, Vinayak Rao

ICML 2019 Benefits and Pitfalls of the Exponential Mechanism with Applications to Hilbert Spaces and Functional PCA Jordan Awan, Ana Kenney, Matthew Reimherr, Aleksandra Slavković

NeurIPS 2019 Elliptical Perturbations for Differential Privacy Matthew Reimherr, Jordan Awan

NeurIPS 2019 KNG: The K-Norm Gradient Mechanism Matthew Reimherr, Jordan Awan

NeurIPS 2018 Differentially Private Uniformly Most Powerful Tests for Binomial Data Jordan Awan, Aleksandra Slavković