Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising

16 May 2018

Papers citing "Improving the Gaussian Mechanism for Differential Privacy: Analytical Calibration and Optimal Denoising"

26 / 26 papers shown

Title
Model Agnostic Differentially Private Causal Inference Christian Lebeda Mathieu Even Aurélien Bellet Julie Josse FedML 33 1 0 26 May 2025
Differential Privacy with Higher Utility by Exploiting Coordinate-wise Disparity: Laplace Mechanism Can Beat Gaussian in High Dimensions Gokularam Muthukrishnan Sheetal Kalyani 107 0 0 28 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 110 5 0 21 Dec 2024
Near Exact Privacy Amplification for Matrix Mechanisms Christopher A. Choquette-Choo Arun Ganesh Saminul Haque Thomas Steinke Abhradeep Thakurta 80 9 0 08 Oct 2024
DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction Xinwei Zhang Zhiqi Bu Borja Balle Mingyi Hong Meisam Razaviyayn Vahab Mirrokni 99 2 0 04 Oct 2024
Rewind-to-Delete: Certified Machine Unlearning for Nonconvex Functions Siqiao Mu Diego Klabjan MU 82 3 0 15 Sep 2024
Gaussian Differentially Private Human Faces Under a Face Radial Curve Representation Carlos Soto M. Reimherr Aleksandra B. Slavkovic Mark Shriver CVBM 44 1 0 10 Sep 2024
Towards Certified Unlearning for Deep Neural Networks Binchi Zhang Yushun Dong Tianhao Wang Wenlin Yao MU 84 8 0 01 Aug 2024
Private Collaborative Edge Inference via Over-the-Air Computation Selim F. Yilmaz Burak Hasircioglu Li Qiao Deniz Gunduz FedML 99 1 0 30 Jul 2024
GCON: Differentially Private Graph Convolutional Network via Objective Perturbation Jianxin Wei Yizheng Zhu Xiaokui Xiao Ergute Bao Yin Yang Kuntai Cai Beng Chin Ooi AAML 73 0 0 06 Jul 2024
Avoiding Pitfalls for Privacy Accounting of Subsampled Mechanisms under Composition C. Lebeda Matthew Regehr Gautam Kamath Thomas Steinke 79 10 0 27 May 2024
FastLloyd: Federated, Accurate, Secure, and Tunable $k$ -Means Clustering with Differential Privacy Abdulrahman Diaa Thomas Humphries Florian Kerschbaum FedML 50 0 0 03 May 2024
Visual Privacy Auditing with Diffusion Models Kristian Schwethelm Johannes Kaiser Moritz Knolle Daniel Rueckert Daniel Rueckert Alexander Ziller DiffM AAML 87 0 0 12 Mar 2024
Private Fine-tuning of Large Language Models with Zeroth-order Optimization Xinyu Tang Ashwinee Panda Milad Nasr Saeed Mahloujifar Prateek Mittal 112 20 0 09 Jan 2024
Differentially Private Synthetic Data via Foundation Model APIs 1: Images Zinan Lin Sivakanth Gopi Janardhan Kulkarni Harsha Nori Sergey Yekhanin 92 38 0 24 May 2023
Differentially Private Learning of Undirected Graphical Models using Collective Graphical Models G. Bernstein Ryan McKenna Tao Sun Daniel Sheldon Michael Hay G. Miklau FedML 42 25 0 14 Jun 2017
Renyi Differential Privacy Ilya Mironov 58 1,243 0 24 Feb 2017
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 175 6,069 0 01 Jul 2016
Privacy Odometers and Filters: Pay-as-you-Go Composition Ryan M. Rogers Aaron Roth Jonathan R. Ullman Salil P. Vadhan 43 108 0 26 May 2016
Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds Mark Bun Thomas Steinke 68 823 0 06 May 2016
Concentrated Differential Privacy Cynthia Dwork G. Rothblum 59 446 0 06 Mar 2016
Understanding the Sparse Vector Technique for Differential Privacy Min Lyu D. Su Ninghui Li 27 164 0 05 Mar 2016
Trend Filtering on Graphs Yu Wang James Sharpnack Alex Smola Robert Tibshirani 42 243 0 28 Oct 2014
The Composition Theorem for Differential Privacy Peter Kairouz Sewoong Oh Pramod Viswanath 93 677 0 04 Nov 2013
Dirichlet draws are sparse with high probability Matus Telgarsky 76 10 0 21 Jan 2013
Detecting Activations over Graphs using Spanning Tree Wavelet Bases James Sharpnack A. Krishnamurthy Aarti Singh 47 53 0 05 Jun 2012