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ORCIDJinshuo Dong
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2020 – today
- 2024
[c10]Jinshuo Dong
, Jason D. Hartline, Liren Shan, Aravindan Vijayaraghavan:
Error-Tolerant E-Discovery Protocols. CSLAW 2024: 24-35- [i13]Jinshuo Dong, Jason D. Hartline, Liren Shan, Aravindan Vijayaraghavan:
Error-Tolerant E-Discovery Protocols. CoRR abs/2401.17952 (2024) - 2022
- [c9]Yuqing Zhu, Jinshuo Dong, Yu-Xiang Wang:
Optimal Accounting of Differential Privacy via Characteristic Function. AISTATS 2022: 4782-4817 - [c8]Jinshuo Dong, Jason D. Hartline, Aravindan Vijayaraghavan:
Classification Protocols with Minimal Disclosure. CSLAW 2022: 67-76 - [c7]Jordan Awan, Jinshuo Dong:
Log-Concave and Multivariate Canonical Noise Distributions for Differential Privacy. NeurIPS 2022 - [i12]Jordan Awan, Jinshuo Dong:
Log-Concave and Multivariate Canonical Noise Distributions for Differential Privacy. CoRR abs/2206.04572 (2022) - [i11]Jinshuo Dong, Jason D. Hartline, Aravindan Vijayaraghavan:
Classification Protocols with Minimal Disclosure. CoRR abs/2209.02690 (2022) - 2021
- [c6]Jinshuo Dong, Weijie J. Su, Linjun Zhang:
A Central Limit Theorem for Differentially Private Query Answering. NeurIPS 2021: 14759-14770 - [c5]Matteo Sordello, Zhiqi Bu, Jinshuo Dong:
Privacy Amplification via Iteration for Shuffled and Online PNSGD. ECML/PKDD (2) 2021: 796-813 - [i10]Jinshuo Dong, Weijie J. Su, Linjun Zhang:
A Central Limit Theorem for Differentially Private Query Answering. CoRR abs/2103.08721 (2021) - [i9]Jinshuo Dong, Aaron Roth, Weijie J. Su:
Rejoinder: Gaussian Differential Privacy. CoRR abs/2104.01987 (2021) - [i8]Yuqing Zhu, Jinshuo Dong, Yu-Xiang Wang:
Optimal Accounting of Differential Privacy via Characteristic Function. CoRR abs/2106.08567 (2021) - [i7]Matteo Sordello, Zhiqi Bu, Jinshuo Dong:
Privacy Amplification via Iteration for Shuffled and Online PNSGD. CoRR abs/2106.11767 (2021) - 2020
- [c4]Jinshuo Dong, David Durfee, Ryan Rogers:
Optimal Differential Privacy Composition for Exponential Mechanisms. ICML 2020: 2597-2606 - [c3]Qinqing Zheng, Jinshuo Dong, Qi Long, Weijie J. Su:
Sharp Composition Bounds for Gaussian Differential Privacy via Edgeworth Expansion. ICML 2020: 11420-11435 - [i6]Qinqing Zheng, Jinshuo Dong, Qi Long, Weijie J. Su:
Sharp Composition Bounds for Gaussian Differential Privacy via Edgeworth Expansion. CoRR abs/2003.04493 (2020)
2010 – 2019
- 2019
- [c2]Jinshuo Dong, Hadi Elzayn, Shahin Jabbari, Michael J. Kearns, Zachary Schutzman:
Equilibrium Characterization for Data Acquisition Games. IJCAI 2019: 252-258 - [i5]Jinshuo Dong, Aaron Roth, Weijie J. Su:
Gaussian Differential Privacy. CoRR abs/1905.02383 (2019) - [i4]Jinshuo Dong, Hadi Elzayn, Shahin Jabbari, Michael J. Kearns, Zachary Schutzman:
Equilibrium Characterization for Data Acquisition Games. CoRR abs/1905.08909 (2019) - [i3]Jinshuo Dong, David Durfee, Ryan Rogers:
Optimal Differential Privacy Composition for Exponential Mechanisms and the Cost of Adaptivity. CoRR abs/1909.13830 (2019) - [i2]Zhiqi Bu, Jinshuo Dong, Qi Long, Weijie J. Su:
Deep Learning with Gaussian Differential Privacy. CoRR abs/1911.11607 (2019) - 2018
- [c1]Jinshuo Dong, Aaron Roth, Zachary Schutzman, Bo Waggoner, Zhiwei Steven Wu:
Strategic Classification from Revealed Preferences. EC 2018: 55-70 - 2017
- [i1]Jinshuo Dong, Aaron Roth, Zachary Schutzman, Bo Waggoner, Zhiwei Steven Wu:
Strategic Classification from Revealed Preferences. CoRR abs/1710.07887 (2017)
Coauthor Index
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