Connect the Dots: Tighter Discrete Approximations of Privacy Loss Distributions

10 July 2022

Papers citing "Connect the Dots: Tighter Discrete Approximations of Privacy Loss Distributions"

30 / 30 papers shown

Title
Empirical Privacy Variance Yuzheng Hu Fan Wu Ruicheng Xian Yuhang Liu Lydia Zakynthinou Pritish Kamath Chiyuan Zhang David A. Forsyth 64 0 0 16 Mar 2025
Adversarial Sample-Based Approach for Tighter Privacy Auditing in Final Model-Only Scenarios Sangyeon Yoon Wonje Jeung Albert No 85 0 0 02 Dec 2024
Scalable DP-SGD: Shuffling vs. Poisson Subsampling Lynn Chua Badih Ghazi Pritish Kamath Ravi Kumar Pasin Manurangsi Amer Sinha Chiyuan Zhang 36 5 0 06 Nov 2024
A Hassle-free Algorithm for Private Learning in Practice: Don't Use Tree Aggregation, Use BLTs H. B. McMahan Zheng Xu Yanxiang Zhang FedML 42 6 0 16 Aug 2024
Fine-Tuning Large Language Models with User-Level Differential Privacy Zachary Charles Arun Ganesh Ryan McKenna H. B. McMahan Nicole Mitchell Krishna Pillutla Keith Rush 39 11 0 10 Jul 2024
Attack-Aware Noise Calibration for Differential Privacy B. Kulynych Juan Felipe Gomez G. Kaissis Flavio du Pin Calmon Carmela Troncoso 57 6 0 02 Jul 2024
Mind the Privacy Unit! User-Level Differential Privacy for Language Model Fine-Tuning Lynn Chua Badih Ghazi Yangsibo Huang Pritish Kamath Ravi Kumar Daogao Liu Pasin Manurangsi Amer Sinha Chiyuan Zhang 32 11 0 20 Jun 2024
Beyond the Calibration Point: Mechanism Comparison in Differential Privacy Georgios Kaissis Stefan Kolek Borja Balle Jamie Hayes Daniel Rueckert 47 4 0 13 Jun 2024
Avoiding Pitfalls for Privacy Accounting of Subsampled Mechanisms under Composition C. Lebeda Matthew Regehr Gautam Kamath Thomas Steinke 53 9 0 27 May 2024
Tighter Privacy Auditing of DP-SGD in the Hidden State Threat Model Tudor Cebere A. Bellet Nicolas Papernot 30 9 0 23 May 2024
pfl-research: simulation framework for accelerating research in Private Federated Learning Filip Granqvist Congzheng Song Áine Cahill Rogier van Dalen Martin Pelikan Yi Sheng Chan Xiaojun Feng Natarajan Krishnaswami Vojta Jina Mona Chitnis FedML 39 6 0 09 Apr 2024
How Private are DP-SGD Implementations? Lynn Chua Badih Ghazi Pritish Kamath Ravi Kumar Pasin Manurangsi Amer Sinha Chiyuan Zhang 43 12 0 26 Mar 2024
Closed-Form Bounds for DP-SGD against Record-level Inference Giovanni Cherubin Boris Köpf Andrew J. Paverd Shruti Tople Lukas Wutschitz Santiago Zanella Béguelin 46 2 0 22 Feb 2024
Privacy Profiles for Private Selection Antti Koskela Rachel Redberg Yu-Xiang Wang 34 1 0 09 Feb 2024
Subsampling is not Magic: Why Large Batch Sizes Work for Differentially Private Stochastic Optimisation Ossi Raisa Joonas Jälkö Antti Honkela 30 6 0 06 Feb 2024
Tight Group-Level DP Guarantees for DP-SGD with Sampling via Mixture of Gaussians Mechanisms Arun Ganesh 26 2 0 17 Jan 2024
Private Fine-tuning of Large Language Models with Zeroth-order Optimization Xinyu Tang Ashwinee Panda Milad Nasr Saeed Mahloujifar Prateek Mittal 47 18 0 09 Jan 2024
Sparsity-Preserving Differentially Private Training of Large Embedding Models Badih Ghazi Yangsibo Huang Pritish Kamath Ravi Kumar Pasin Manurangsi Amer Sinha Chiyuan Zhang 29 2 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 27 13 0 21 Aug 2023
The importance of feature preprocessing for differentially private linear optimization Ziteng Sun A. Suresh A. Menon 30 3 0 19 Jul 2023
DP-Auditorium: a Large Scale Library for Auditing Differential Privacy William Kong Andrés Munoz Medina Mónica Ribero Umar Syed 29 2 0 10 Jul 2023
Bounding data reconstruction attacks with the hypothesis testing interpretation of differential privacy Georgios Kaissis Jamie Hayes Alexander Ziller Daniel Rueckert AAML 41 11 0 08 Jul 2023
DPAF: Image Synthesis via Differentially Private Aggregation in Forward Phase Chih-Hsun Lin Chia-Yi Hsu Chia-Mu Yu Yang Cao Chun-ying Huang 36 1 0 20 Apr 2023
A Randomized Approach for Tight Privacy Accounting Jiachen T. Wang Saeed Mahloujifar Tong Wu R. Jia Prateek Mittal 36 9 0 17 Apr 2023
Private Ad Modeling with DP-SGD Carson E. Denison Badih Ghazi Pritish Kamath Ravi Kumar Pasin Manurangsi Krishnagiri Narra Amer Sinha A. Varadarajan Chiyuan Zhang 32 14 0 21 Nov 2022
Learning to Generate Image Embeddings with User-level Differential Privacy Zheng Xu Maxwell D. Collins Yuxiao Wang Liviu Panait Sewoong Oh S. Augenstein Ting Liu Florian Schroff H. B. McMahan FedML 30 29 0 20 Nov 2022
The Saddle-Point Accountant for Differential Privacy Wael Alghamdi S. Asoodeh Flavio du Pin Calmon Juan Felipe Gomez O. Kosut Lalitha Sankar Fei Wei 25 7 0 20 Aug 2022
Faster Privacy Accounting via Evolving Discretization Badih Ghazi Pritish Kamath Ravi Kumar Pasin Manurangsi 65 14 0 10 Jul 2022
Bayesian Estimation of Differential Privacy Santiago Zanella Béguelin Lukas Wutschitz Shruti Tople A. Salem Victor Rühle Andrew J. Paverd Mohammad Naseri Boris Köpf Daniel Jones 19 36 0 10 Jun 2022
Individual Privacy Accounting via a Renyi Filter Vitaly Feldman Tijana Zrnic 59 86 0 25 Aug 2020