Rényi Differential Privacy of the Sampled Gaussian Mechanism

28 August 2019

Papers citing "Rényi Differential Privacy of the Sampled Gaussian Mechanism"

50 / 177 papers shown

Title
DP-AdamBC: Your DP-Adam Is Actually DP-SGD (Unless You Apply Bias Correction) Qiaoyue Tang Frederick Shpilevskiy Mathias Lécuyer 43 14 0 21 Dec 2023
Differentially Private SGD Without Clipping Bias: An Error-Feedback Approach Xinwei Zhang Zhiqi Bu Zhiwei Steven Wu Mingyi Hong 22 7 0 24 Nov 2023
DPSUR: Accelerating Differentially Private Stochastic Gradient Descent Using Selective Update and Release Jie Fu Qingqing Ye Haibo Hu Zhili Chen Lulu Wang Kuncan Wang Xun Ran 26 14 0 23 Nov 2023
Preserving Node-level Privacy in Graph Neural Networks Zihang Xiang Tianhao Wang Di Wang 27 6 0 12 Nov 2023
Unified Enhancement of Privacy Bounds for Mixture Mechanisms via $f$ -Differential Privacy Chendi Wang Buxin Su Jiayuan Ye Reza Shokri Weijie J. Su FedML 21 10 0 30 Oct 2023
DP-SGD with weight clipping Antoine Barczewski Jan Ramon 11 1 0 27 Oct 2023
Privacy Amplification for Matrix Mechanisms Christopher A. Choquette-Choo Arun Ganesh Thomas Steinke Abhradeep Thakurta 30 10 0 24 Oct 2023
PrivImage: Differentially Private Synthetic Image Generation using Diffusion Models with Semantic-Aware Pretraining Kecen Li Chen Gong Zhixiang Li Yuzhong Zhao Xinwen Hou Tianhao Wang 33 10 0 19 Oct 2023
Differentially Private Data Generation with Missing Data Shubhankar Mohapatra Jianqiao Zong F. Kerschbaum Xi He SyDa 17 1 0 17 Oct 2023
A Unified View of Differentially Private Deep Generative Modeling Dingfan Chen Raouf Kerkouche Mario Fritz SyDa 33 4 0 27 Sep 2023
PA-iMFL: Communication-Efficient Privacy Amplification Method against Data Reconstruction Attack in Improved Multi-Layer Federated Learning Jianhua Wang Xiaolin Chang Jelena Mivsić Vojislav B. Mivsić Zhi Chen Junchao Fan 43 2 0 25 Sep 2023
Communication Efficient Private Federated Learning Using Dithering Burak Hasircioglu Deniz Gunduz FedML 45 7 0 14 Sep 2023
Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning Zebang Shen Jiayuan Ye Anmin Kang Hamed Hassani Reza Shokri FedML 45 16 0 11 Sep 2023
Geometry of Sensitivity: Twice Sampling and Hybrid Clipping in Differential Privacy with Optimal Gaussian Noise and Application to Deep Learning Hanshen Xiao Jun Wan Srini Devadas 14 7 0 06 Sep 2023
ULDP-FL: Federated Learning with Across Silo User-Level Differential Privacy Fumiyuki Kato Li Xiong Shun Takagi Yang Cao Masatoshi Yoshikawa FedML 25 3 0 23 Aug 2023
ALI-DPFL: Differentially Private Federated Learning with Adaptive Local Iterations Xinpeng Ling Jie Fu Kuncan Wang Haitao Liu Zhili Chen FedML 39 2 0 21 Aug 2023
Differential Privacy, Linguistic Fairness, and Training Data Influence: Impossibility and Possibility Theorems for Multilingual Language Models Phillip Rust Anders Søgaard 33 3 0 17 Aug 2023
Enhancing the Antidote: Improved Pointwise Certifications against Poisoning Attacks Shijie Liu Andrew C. Cullen Paul Montague S. Erfani Benjamin I. P. Rubinstein AAML 26 3 0 15 Aug 2023
Large-Scale Public Data Improves Differentially Private Image Generation Quality Ruihan Wu Chuan Guo Kamalika Chaudhuri 29 2 0 04 Aug 2023
Samplable Anonymous Aggregation for Private Federated Data Analysis Kunal Talwar Shan Wang Audra McMillan Vojta Jina Vitaly Feldman ... Congzheng Song Karl Tarbe Sebastian Vogt L. Winstrom Shundong Zhou FedML 38 13 0 27 Jul 2023
Spectral-DP: Differentially Private Deep Learning through Spectral Perturbation and Filtering Ce Feng Nuo Xu Wujie Wen Parv Venkitasubramaniam Caiwen Ding 12 4 0 25 Jul 2023
Population Expansion for Training Language Models with Private Federated Learning Tatsuki Koga Congzheng Song Martin Pelikan Mona Chitnis FedML 24 1 0 14 Jul 2023
Personalized Privacy Amplification via Importance Sampling Dominik Fay Sebastian Mair Jens Sjölund 63 0 0 05 Jul 2023
Gradients Look Alike: Sensitivity is Often Overestimated in DP-SGD Anvith Thudi Hengrui Jia Casey Meehan Ilia Shumailov Nicolas Papernot 33 3 0 01 Jul 2023
ViP: A Differentially Private Foundation Model for Computer Vision Yaodong Yu Maziar Sanjabi Yi Ma Kamalika Chaudhuri Chuan Guo 21 12 0 15 Jun 2023
Augment then Smooth: Reconciling Differential Privacy with Certified Robustness Jiapeng Wu Atiyeh Ashari Ghomi David Glukhov Jesse C. Cresswell Franziska Boenisch Nicolas Papernot AAML 45 1 0 14 Jun 2023
Differentially Private Wireless Federated Learning Using Orthogonal Sequences Xizixiang Wei Tianhao Wang Ruiquan Huang Cong Shen Jing Yang H. Vincent Poor 48 1 0 14 Jun 2023
(Amplified) Banded Matrix Factorization: A unified approach to private training Christopher A. Choquette-Choo Arun Ganesh Ryan McKenna H. B. McMahan Keith Rush Abhradeep Thakurta Zheng Xu FedML 33 36 0 13 Jun 2023
Privately generating tabular data using language models Alexandre Sablayrolles Yue Wang Brian Karrer LMTD 26 4 0 07 Jun 2023
DP-SGD Without Clipping: The Lipschitz Neural Network Way Louis Bethune Thomas Massena Thibaut Boissin Yannick Prudent Corentin Friedrich Franck Mamalet A. Bellet M. Serrurier David Vigouroux 34 9 0 25 May 2023
Faster Differentially Private Convex Optimization via Second-Order Methods Arun Ganesh Mahdi Haghifam Thomas Steinke Abhradeep Thakurta 19 10 0 22 May 2023
Privacy Auditing with One (1) Training Run Thomas Steinke Milad Nasr Matthew Jagielski 53 77 0 15 May 2023
DPMLBench: Holistic Evaluation of Differentially Private Machine Learning Chengkun Wei Ming-Hui Zhao Zhikun Zhang Min Chen Wenlong Meng Bodong Liu Yuan-shuo Fan Wenzhi Chen 34 11 0 10 May 2023
Practical Differentially Private and Byzantine-resilient Federated Learning Zihang Xiang Tianhao Wang Wanyu Lin Di Wang FedML 36 21 0 15 Apr 2023
Gradient Sparsification for Efficient Wireless Federated Learning with Differential Privacy Kang Wei Jun Li Chuan Ma Ming Ding Feng Shu Haitao Zhao Wen Chen Hongbo Zhu FedML 35 4 0 09 Apr 2023
Have it your way: Individualized Privacy Assignment for DP-SGD Franziska Boenisch Christopher Muhl Adam Dziedzic Roy Rinberg Nicolas Papernot 18 18 0 29 Mar 2023
How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy Natalia Ponomareva Hussein Hazimeh Alexey Kurakin Zheng Xu Carson E. Denison H. B. McMahan Sergei Vassilvitskii Steve Chien Abhradeep Thakurta 99 167 0 01 Mar 2023
From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning Edwige Cyffers A. Bellet D. Basu FedML 29 5 0 24 Feb 2023
Private GANs, Revisited Alex Bie Gautam Kamath Guojun Zhang 38 14 0 06 Feb 2023
$z$ -SignFedAvg: A Unified Stochastic Sign-based Compression for Federated Learning Zhiwei Tang Yanmeng Wang Tsung-Hui Chang FedML 27 14 0 06 Feb 2023
FedLAP-DP: Federated Learning by Sharing Differentially Private Loss Approximations Hui-Po Wang Dingfan Chen Raouf Kerkouche Mario Fritz FedML DD 26 4 0 02 Feb 2023
Equivariant Differentially Private Deep Learning: Why DP-SGD Needs Sparser Models Florian A. Hölzl Daniel Rueckert Georgios Kaissis 32 4 0 30 Jan 2023
Practical Differentially Private Hyperparameter Tuning with Subsampling A. Koskela Tejas D. Kulkarni 41 14 0 27 Jan 2023
Differentially Private Natural Language Models: Recent Advances and Future Directions Lijie Hu Ivan Habernal Lei Shen Di Wang AAML 35 18 0 22 Jan 2023
Skellam Mixture Mechanism: a Novel Approach to Federated Learning with Differential Privacy Ergute Bao Yizheng Zhu X. Xiao Yifan Yang Beng Chin Ooi B. Tan Khin Mi Mi Aung FedML 31 19 0 08 Dec 2022
Differentially Private Adaptive Optimization with Delayed Preconditioners Tian Li Manzil Zaheer Ziyu Liu Sashank J. Reddi H. B. McMahan Virginia Smith 50 10 0 01 Dec 2022
Adap DP-FL: Differentially Private Federated Learning with Adaptive Noise Jie Fu Zhili Chen Xiao Han FedML 25 28 0 29 Nov 2022
Differentially Private Image Classification from Features Harsh Mehta Walid Krichene Abhradeep Thakurta Alexey Kurakin Ashok Cutkosky 58 7 0 24 Nov 2022
SA-DPSGD: Differentially Private Stochastic Gradient Descent based on Simulated Annealing Jie Fu Zhili Chen Xinpeng Ling 27 0 0 14 Nov 2022
Private Set Generation with Discriminative Information Dingfan Chen Raouf Kerkouche Mario Fritz DD 30 34 0 07 Nov 2022