Individual Privacy Accounting via a Renyi Filter

25 August 2020

Papers citing "Individual Privacy Accounting via a Renyi Filter"

23 / 23 papers shown

Title
Controlled privacy leakage propagation throughout overlapping grouped learning Shahrzad Kiani Franziska Boenisch S. Draper FedML 72 0 0 06 Mar 2025
On the Differential Privacy and Interactivity of Privacy Sandbox Reports Badih Ghazi Charlie Harrison Arpana Hosabettu Pritish Kamath Alexander Knop ... Ethan Leeman Pasin Manurangsi Vikas Sahu Vikas Sahu Phillipp Schoppmann 92 1 0 22 Dec 2024
Differentially Private Block-wise Gradient Shuffle for Deep Learning Zilong Zhang FedML 27 0 0 31 Jul 2024
Cross-silo Federated Learning with Record-level Personalized Differential Privacy Junxu Liu Jian Lou Li Xiong Jinfei Liu Xiaofeng Meng 25 5 0 29 Jan 2024
Personalized Privacy Amplification via Importance Sampling Dominik Fay Sebastian Mair Jens Sjölund 54 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 24 3 0 01 Jul 2023
Multi-Task Differential Privacy Under Distribution Skew Walid Krichene Prateek Jain Shuang Song Mukund Sundararajan Abhradeep Thakurta Li Zhang FedML 32 3 0 15 Feb 2023
Bounding Training Data Reconstruction in DP-SGD Jamie Hayes Saeed Mahloujifar Borja Balle AAML FedML 33 39 0 14 Feb 2023
Composition of Differential Privacy & Privacy Amplification by Subsampling Thomas Steinke 56 49 0 02 Oct 2022
Bayesian and Frequentist Semantics for Common Variations of Differential Privacy: Applications to the 2020 Census Daniel Kifer John M. Abowd Robert Ashmead Ryan Cumings-Menon Philip Leclerc Ashwin Machanavajjhala William Sexton Pavel I Zhuravlev 46 26 0 07 Sep 2022
Connect the Dots: Tighter Discrete Approximations of Privacy Loss Distributions Vadym Doroshenko Badih Ghazi Pritish Kamath Ravi Kumar Pasin Manurangsi 16 40 0 10 Jul 2022
Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints Justin Whitehouse Zhiwei Steven Wu Aaditya Ramdas Ryan M. Rogers 11 9 0 15 Jun 2022
$Privacy accounting $\varepsilon$conomics: Improving differential privacy composition via a posteriori bounds$ Privacy accounting $\varepsilon$ conomics: Improving differential privacy composition via a posteriori bounds Valentin Hartmann Vincent Bindschaedler Alexander Bentkamp Robert West 16 1 0 06 May 2022
Reconstructing Training Data with Informed Adversaries Borja Balle Giovanni Cherubin Jamie Hayes MIACV AAML 32 158 0 13 Jan 2022
Privately Publishable Per-instance Privacy Rachel Redberg Yu-Xiang Wang 29 17 0 03 Nov 2021
Not all noise is accounted equally: How differentially private learning benefits from large sampling rates Friedrich Dörmann Osvald Frisk L. Andersen Christian Fischer Pedersen FedML 56 25 0 12 Oct 2021
Towards General-purpose Infrastructure for Protecting Scientific Data Under Study Andrew Trask Kritika Prakash 35 3 0 04 Oct 2021
Opacus: User-Friendly Differential Privacy Library in PyTorch Ashkan Yousefpour I. Shilov Alexandre Sablayrolles Davide Testuggine Karthik Prasad ... Sayan Gosh Akash Bharadwaj Jessica Zhao Graham Cormode Ilya Mironov VLM 152 349 0 25 Sep 2021
An automatic differentiation system for the age of differential privacy Dmitrii Usynin Alexander Ziller Moritz Knolle Andrew Trask Kritika Prakash Daniel Rueckert Georgios Kaissis 23 3 0 22 Sep 2021
DDUO: General-Purpose Dynamic Analysis for Differential Privacy Chiké Abuah Alex Silence David Darais Joseph P. Near 40 12 0 16 Mar 2021
Deep Learning with Label Differential Privacy Badih Ghazi Noah Golowich Ravi Kumar Pasin Manurangsi Chiyuan Zhang 39 144 0 11 Feb 2021
The Sparse Vector Technique, Revisited Haim Kaplan Yishay Mansour Uri Stemmer 30 17 0 02 Oct 2020
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 141 420 0 29 Nov 2018