Jordan Awan

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 25

Top Topics

Differential Privacy

Statistical Inference

Top Venues

J. Priv. Confidentiality

J. Mach. Learn. Res.

Publications

Jordan Awan, Olivier Bernardi
Tutte polynomials for regular oriented matroids. Discret. Math. 347 (1) (2024)
Jordan Awan, Andres Felipe Barrientos, Nianqiao Ju
Statistical Inference for Privatized Data with Unknown Sample Size. CoRR (2024)
Taegyu Kang, Sehwan Kim, Jinwon Sohn, Jordan Awan
Differentially Private Topological Data Analysis. CoRR (2023)
Jordan Awan, Aishwarya Ramasethu
Optimizing Noise for f-Differential Privacy via Anti-Concentration and Stochastic Dominance. CoRR (2023)
Jordan Awan, Zhanyu Wang
Simulation-based, Finite-sample Inference for Privatized Data. CoRR (2023)
Jordan Awan, Vinayak Rao
Privacy-Aware Rejection Sampling. J. Mach. Learn. Res. 24 (2023)
Jordan Awan, Jinshuo Dong
Log-Concave and Multivariate Canonical Noise Distributions for Differential Privacy. NeurIPS (2022)
Jordan Awan, Claire Frechette, Yumi Li, Elizabeth W. McMahon
Demicaps in AG(4, 3) and Maximal Cap Partitions. Graphs Comb. 38 (6) (2022)
Jordan Awan, Yue Wang
Differentially Private Kolmogorov-Smirnov-Type Tests. CoRR (2022)
Jordan Awan, Jinshuo Dong
Log-Concave and Multivariate Canonical Noise Distributions for Differential Privacy. CoRR (2022)
Nianqiao Ju, Jordan Awan, Ruobin Gong, Vinayak Rao
Data Augmentation MCMC for Bayesian Inference from Privatized Data. NeurIPS (2022)
Zhanyu Wang, Guang Cheng, Jordan Awan
Differentially Private Bootstrap: New Privacy Analysis and Inference Strategies. CoRR (2022)
Jordan Awan, Vinayak Rao
Privacy-Aware Rejection Sampling. CoRR (2021)
Jordan Awan, Salil P. Vadhan
Canonical Noise Distributions and Private Hypothesis Tests. CoRR (2021)
Jordan Awan, Aleksandra B. Slavkovic
Differentially Private Inference for Binomial Data. J. Priv. Confidentiality 10 (1) (2020)
Jordan Awan, Olivier Bernardi
Tutte polynomials for directed graphs. J. Comb. Theory, Ser. B 140 (2020)
Jordan Awan, Zhanrui Cai
One Step to Efficient Synthetic Data. CoRR (2020)
Jordan Awan, Ana Kenney, Matthew Reimherr, Aleksandra B. Slavkovic
Benefits and Pitfalls of the Exponential Mechanism with Applications to Hilbert Spaces and Functional PCA. CoRR (2019)
Jordan Awan, Aleksandra B. Slavkovic
Differentially Private Inference for Binomial Data. CoRR (2019)
Matthew Reimherr, Jordan Awan
Elliptical Perturbations for Differential Privacy. CoRR (2019)
Jordan Awan, Ana Kenney, Matthew Reimherr, Aleksandra B. Slavkovic
Benefits and Pitfalls of the Exponential Mechanism with Applications to Hilbert Spaces and Functional PCA. ICML (2019)
Matthew Reimherr, Jordan Awan
KNG: The K-Norm Gradient Mechanism. CoRR (2019)
Matthew Reimherr, Jordan Awan
Elliptical Perturbations for Differential Privacy. NeurIPS (2019)
Matthew Reimherr, Jordan Awan
KNG: The K-Norm Gradient Mechanism. NeurIPS (2019)
Jordan Awan, Aleksandra B. Slavkovic
Differentially Private Uniformly Most Powerful Tests for Binomial Data. NeurIPS (2018)