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The Composition Theorem for Differential Privacy

4 November 2013

Peter Kairouz

Sewoong Oh

Pramod Viswanath

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Papers citing "The Composition Theorem for Differential Privacy"

22 / 22 papers shown

Title
Empirical Privacy Variance Yuzheng Hu Fan Wu Ruicheng Xian Yuhang Liu Lydia Zakynthinou Pritish Kamath Chiyuan Zhang David A. Forsyth 132 0 0 16 Mar 2025
Enhancing Privacy in the Early Detection of Sexual Predators Through Federated Learning and Differential Privacy Khaoula Chehbouni Martine De Cock Gilles Caporossi Afaf Taik Reihaneh Rabbany G. Farnadi 145 1 0 21 Jan 2025
Safeguarding System Prompts for LLMs Zhifeng Jiang Zhihua Jin Guoliang He AAML SILM 139 2 0 10 Jan 2025
Differentially Private Online Federated Learning with Correlated Noise Jiaojiao Zhang Linglingzhi Zhu Mikael Johansson FedML 98 1 0 10 Jan 2025
Balls-and-Bins Sampling for DP-SGD Lynn Chua Badih Ghazi Charlie Harrison Ethan Leeman Pritish Kamath Ravi Kumar Pasin Manurangsi Amer Sinha Chiyuan Zhang 146 6 0 21 Dec 2024
Adversarial Sample-Based Approach for Tighter Privacy Auditing in Final Model-Only Scenarios Sangyeon Yoon Wonje Jeung Albert No 176 0 0 02 Dec 2024
The 2020 United States Decennial Census Is More Private Than You (Might) Think Buxin Su Weijie J. Su Chendi Wang 65 3 0 11 Oct 2024
Differentially Private Block-wise Gradient Shuffle for Deep Learning Zilong Zhang FedML 89 0 0 31 Jul 2024
Privacy of the last iterate in cyclically-sampled DP-SGD on nonconvex composite losses Weiwei Kong Mónica Ribero 78 4 0 07 Jul 2024
Differentially Private Graph Diffusion with Applications in Personalized PageRanks Rongzhe Wei Eli Chien P. Li 105 6 0 22 Jun 2024
Private Online Learning via Lazy Algorithms Hilal Asi Tomer Koren Daogao Liu Kunal Talwar 207 1 0 05 Jun 2024
Avoiding Pitfalls for Privacy Accounting of Subsampled Mechanisms under Composition C. Lebeda Matthew Regehr Gautam Kamath Thomas Steinke 118 10 0 27 May 2024
Tighter Privacy Auditing of DP-SGD in the Hidden State Threat Model Tudor Cebere A. Bellet Nicolas Papernot 93 13 0 23 May 2024
Private Fine-tuning of Large Language Models with Zeroth-order Optimization Xinyu Tang Ashwinee Panda Milad Nasr Saeed Mahloujifar Prateek Mittal 191 26 0 09 Jan 2024
Concurrent Composition for Interactive Differential Privacy with Adaptive Privacy-Loss Parameters Samuel Haney Michael Shoemate Grace Tian Salil P. Vadhan Andrew Vyrros Vicki Xu Wanrong Zhang 68 6 0 12 Sep 2023
Personalized Privacy Amplification via Importance Sampling Dominik Fay Sebastian Mair Jens Sjölund 119 0 0 05 Jul 2023
Privacy Amplification for Federated Learning via User Sampling and Wireless Aggregation Mohamed Seif Wei-Ting Chang Ravi Tandon FedML 96 46 0 02 Mar 2021
Noiseless Privacy F. Farokhi 56 9 0 29 Oct 2019
The Optimal Mechanism in Differential Privacy: Multidimensional Setting Quan Geng Pramod Viswanath 131 124 0 02 Dec 2013
Iterative Constructions and Private Data Release Anupam Gupta Aaron Roth Jonathan R. Ullman 96 208 0 19 Jul 2011
On the Geometry of Differential Privacy Moritz Hardt Kunal Talwar 135 464 0 21 Jul 2009
A statistical framework for differential privacy Larry A. Wasserman Shuheng Zhou 138 486 0 16 Nov 2008