Strategic Classification from Revealed Preferences. - Jinshuo Dong; Aaron Roth 001; Zachary Schutzman; Bo Waggoner; Zhiwei Steven Wu (EC, 2018)

Equilibrium Characterization for Data Acquisition Games. - Jinshuo Dong; Hadi Elzayn; Shahin Jabbari; Michael J. Kearns; Zachary Schutzman (IJCAI, 2019)

Gaussian Differential Privacy. - Jinshuo Dong; Aaron Roth 001; Weijie J. Su (CoRR, 2019)

Optimal Differential Privacy Composition for Exponential Mechanisms and the Cost of Adaptivity. - Jinshuo Dong; David Durfee; Ryan Rogers 002 (CoRR, 2019)

Deep Learning with Gaussian Differential Privacy. - Zhiqi Bu; Jinshuo Dong; Qi Long; Weijie J. Su (CoRR, 2019)

Optimal Differential Privacy Composition for Exponential Mechanisms. - Jinshuo Dong; David Durfee; Ryan Rogers 002 (ICML, 2020)

Sharp Composition Bounds for Gaussian Differential Privacy via Edgeworth Expansion. - Qinqing Zheng; Jinshuo Dong; Qi Long; Weijie J. Su (ICML, 2020)

A Central Limit Theorem for Differentially Private Query Answering. - Jinshuo Dong; Weijie J. Su; Linjun Zhang (NeurIPS, 2021)

Privacy Amplification via Iteration for Shuffled and Online PNSGD. - Matteo Sordello; Zhiqi Bu; Jinshuo Dong (ECML/PKDD (2), 2021)

Rejoinder: Gaussian Differential Privacy. - Jinshuo Dong; Aaron Roth 001; Weijie J. Su (CoRR, 2021)

Optimal Accounting of Differential Privacy via Characteristic Function. - Yuqing Zhu 005; Jinshuo Dong; Yu-Xiang Wang 003 (AISTATS, 2022)

Classification Protocols with Minimal Disclosure. - Jinshuo Dong; Jason D. Hartline; Aravindan Vijayaraghavan (CSLAW, 2022)

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

Error-Tolerant E-Discovery Protocols. - Jinshuo Dong; Jason D. Hartline; Liren Shan; Aravindan Vijayaraghavan (CSLAW, 2024)