Not all noise is accounted equally: How differentially private learning
benefits from large sampling rates

Not all noise is accounted equally: How differentially private learning benefits from large sampling rates

12 October 2021

Friedrich Dörmann

Christian Fischer Pedersen

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Papers citing "Not all noise is accounted equally: How differentially private learning benefits from large sampling rates"

18 / 18 papers shown

Title
Towards Reliable and Generalizable Differentially Private Machine Learning (Extended Version) Wenxuan Bao Vincent Bindschaedler AAML 56 0 0 21 Aug 2025
Forward Learning with Differential Privacy Mingqian Feng Zeliang Zhang Jinyang Jiang Yijie Peng Chenliang Xu 125 0 0 01 Apr 2025
The Impact of Generalization Techniques on the Interplay Among Privacy, Utility, and Fairness in Image Classification Ahmad Hassanpour Amir Zarei Khawla Mallat Anderson Santana de Oliveira Bian Yang 157 0 0 16 Dec 2024
R+R:Understanding Hyperparameter Effects in DP-SGD Felix Morsbach J. Reubold T. Strufe 111 0 0 04 Nov 2024
Masked Differential Privacy David Schneider Sina Sajadmanesh Vikash Sehwag Saquib Sarfraz Rainer Stiefelhagen Lingjuan Lyu Vivek Sharma 92 1 0 22 Oct 2024
Nearly Tight Black-Box Auditing of Differentially Private Machine Learning Meenatchi Sundaram Muthu Selva Annamalai Emiliano De Cristofaro 142 15 0 23 May 2024
Sparsity-Preserving Differentially Private Training of Large Embedding Models Badih Ghazi Yangsibo Huang Pritish Kamath Ravi Kumar Pasin Manurangsi Amer Sinha Chiyuan Zhang 89 3 0 14 Nov 2023
Unlocking Accuracy and Fairness in Differentially Private Image Classification Leonard Berrada Soham De J. Shen Jamie Hayes Robert Stanforth David Stutz Pushmeet Kohli Samuel L. Smith Borja Balle 100 16 0 21 Aug 2023
Differentially Private Video Activity Recognition Zelun Luo Yuliang Zou Yijin Yang Zane Durante De-An Huang Zhiding Yu Chaowei Xiao L. Fei-Fei Anima Anandkumar PICV 101 5 0 27 Jun 2023
Differentially Private Image Classification by Learning Priors from Random Processes Xinyu Tang Ashwinee Panda Vikash Sehwag Prateek Mittal 121 26 0 08 Jun 2023
Equivariant Differentially Private Deep Learning: Why DP-SGD Needs Sparser Models Florian A. Hölzl Daniel Rueckert Georgios Kaissis 145 4 0 30 Jan 2023
Differentially Private Image Classification from Features Harsh Mehta Walid Krichene Abhradeep Thakurta Alexey Kurakin Ashok Cutkosky 145 10 0 24 Nov 2022
Differentially Private Diffusion Models Tim Dockhorn Tianshi Cao Arash Vahdat Karsten Kreis DiffM 146 114 0 18 Oct 2022
Kernel Normalized Convolutional Networks for Privacy-Preserving Machine Learning Reza Nasirigerdeh Javad Torkzadehmahani Daniel Rueckert Georgios Kaissis 108 1 0 30 Sep 2022
SmoothNets: Optimizing CNN architecture design for differentially private deep learning Nicolas W. Remerscheid Alexander Ziller Daniel Rueckert Georgios Kaissis 59 7 0 09 May 2022
Large Scale Transfer Learning for Differentially Private Image Classification Harsh Mehta Abhradeep Thakurta Alexey Kurakin Ashok Cutkosky 121 45 0 06 May 2022
Unlocking High-Accuracy Differentially Private Image Classification through Scale Soham De Leonard Berrada Jamie Hayes Samuel L. Smith Borja Balle 157 244 0 28 Apr 2022
Differentially private training of residual networks with scale normalisation Helena Klause Alexander Ziller Daniel Rueckert Kerstin Hammernik Georgios Kaissis 123 35 0 01 Mar 2022