Gaussian differential privacy J Dong, A Roth, WJ Su Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2021 | 246 | 2021 |
Deep learning with gaussian differential privacy Z Bu, J Dong, Q Long, WJ Su Harvard data science review 2020 (23), 10.1162/99608f92. cfc5dd25, 2020 | 138 | 2020 |
Strategic classification from revealed preferences J Dong, A Roth, Z Schutzman, B Waggoner, ZS Wu Proceedings of the 2018 ACM Conference on Economics and Computation, 55-70, 2018 | 122 | 2018 |
Optimal accounting of differential privacy via characteristic function Y Zhu, J Dong, YX Wang International Conference on Artificial Intelligence and Statistics, 4782-4817, 2022 | 39 | 2022 |
Optimal differential privacy composition for exponential mechanisms J Dong, D Durfee, R Rogers International Conference on Machine Learning, 2597-2606, 2020 | 38 | 2020 |
Sharp composition bounds for Gaussian differential privacy via edgeworth expansion Q Zheng, J Dong, Q Long, W Su International Conference on Machine Learning, 11420-11435, 2020 | 10 | 2020 |
Su. 2019. Gaussian differential privacy J Dong, A Roth, J Weijie arXiv preprint arXiv:1905.02383, 2019 | 8 | 2019 |
Privacy amplification via iteration for shuffled and online PNSGD M Sordello, Z Bu, J Dong Machine Learning and Knowledge Discovery in Databases. Research Track …, 2021 | 5 | 2021 |
A Central Limit Theorem for Differentially Private Query Answering J Dong, WJ Su, L Zhang NeurIPS 2021, 2021 | 4 | 2021 |
Equilibrium Characterization for Data Acquisition Games J Dong, H Elzayn, S Jabbari, M Kearns, Z Schutzman Proceedings of the Twenty-Eighth International Joint Conference on …, 2019 | 3 | 2019 |
Rejoinder: Gaussian Differential Privacy J Dong, A Roth, WJ Su arXiv preprint arXiv:2104.01987, 2021 | 2 | 2021 |
Log-Concave and Multivariate Canonical Noise Distributions for Differential Privacy J Awan, J Dong arXiv preprint arXiv:2206.04572, 2022 | 1 | 2022 |
Classification Protocols with Minimal Disclosure J Dong, J Hartline, A Vijayaraghavan Proceedings of the 2022 Symposium on Computer Science and Law, 67-76, 2022 | | 2022 |
Authors’ Reply to the Discussion of ‘Gaussian Differential Privacy’ by Dong et al. J Dong, A Roth, WJ Su Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2022 | | 2022 |
Gaussian Differential Privacy and Related Techniques J Dong University of Pennsylvania, 2020 | | 2020 |
RSS Written Discussion for December 16, 2020 J Dong, A Roth, WJ Su | | |
Optimal Differential Privacy Composition for Exponential Mechanisms: Supplementary Materials J Dong, D Durfee, R Rogers | | |
Limiting properties on the number of leaves in Barabasi-Albert Model L Zhang, J Dong | | |
A NOTE ON THE MAXIMUM OF RANDOM WALK WITH NEGATIVE DRIFT L ZHANG, J DONG | | |