User-level Differentially Private Stochastic Convex Optimization: Efficient Algorithms with Optimal Rates

7 November 2023

Papers citing "User-level Differentially Private Stochastic Convex Optimization: Efficient Algorithms with Optimal Rates"

9 / 9 papers shown

Title
Towards User-level Private Reinforcement Learning with Human Feedback J. Zhang Mingxi Lei Meng Ding Mengdi Li Zihang Xiang Difei Xu Jinhui Xu Di Wang 42 0 0 22 Feb 2025
Characterizing the Accuracy-Communication-Privacy Trade-off in Distributed Stochastic Convex Optimization Sudeep Salgia Nikola Pavlovic Yuejie Chi Qing Zhao 39 0 0 06 Jan 2025
Faster Algorithms for User-Level Private Stochastic Convex Optimization Andrew Lowy Daogao Liu Hilal Asi 28 0 0 24 Oct 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 31 11 0 10 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 24 11 0 20 Jun 2024
Private Stochastic Convex Optimization with Heavy Tails: Near-Optimality from Simple Reductions Hilal Asi Daogao Liu Kevin Tian 32 3 0 04 Jun 2024
Learning with User-Level Local Differential Privacy Puning Zhao Li Shen Rongfei Fan Qingming Li Huiwen Wu Jiafei Wu Zhe Liu 27 2 0 27 May 2024
A Huber Loss Minimization Approach to Mean Estimation under User-level Differential Privacy Puning Zhao Lifeng Lai Li Shen Qingming Li Jiafei Wu Zhe Liu 47 7 0 22 May 2024
Private Stochastic Optimization With Large Worst-Case Lipschitz Parameter: Optimal Rates for (Non-Smooth) Convex Losses and Extension to Non-Convex Losses Andrew Lowy Meisam Razaviyayn 30 13 0 15 Sep 2022