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Learning with User-Level Privacy

23 February 2021

Papers citing "Learning with User-Level Privacy"

50 / 65 papers shown

Title
Black-Box Privacy Attacks on Shared Representations in Multitask Learning John Abascal Nicolás Berrios Alina Oprea Jonathan R. Ullman Adam D. Smith Matthew Jagielski MLAU 16 0 0 19 Jun 2025
Nosy Layers, Noisy Fixes: Tackling DRAs in Federated Learning Systems using Explainable AI Meghali Nandi Arash Shaghaghi Nazatul Haque Sultan Gustavo Batista Raymond K. Zhao Sanjay Jha AAML 167 0 0 16 May 2025
Video-DPRP: A Differentially Private Approach for Visual Privacy-Preserving Video Human Activity Recognition Allassan Tchangmena A Nken Susan Mckeever Peter Corcoran Ihsan Ullah PICV 96 0 0 03 Mar 2025
Towards User-level Private Reinforcement Learning with Human Feedback Jing Zhang Mingxi Lei Meng Ding Mengdi Li Zihang Xiang Difei Xu Jinhui Xu Di Wang 107 3 0 22 Feb 2025
Characterizing the Accuracy-Communication-Privacy Trade-off in Distributed Stochastic Convex Optimization Sudeep Salgia Nikola Pavlovic Yuejie Chi Qing Zhao 114 0 0 06 Jan 2025
Faster Algorithms for User-Level Private Stochastic Convex Optimization Andrew Lowy Daogao Liu Hilal Asi 53 1 0 24 Oct 2024
Calibrating Noise for Group Privacy in Subsampled Mechanisms Yangfan Jiang Xinjian Luo Yin Yang Xiaokui Xiao 97 3 0 19 Aug 2024
Private Means and the Curious Incident of the Free Lunch Jack Fitzsimons James Honaker Michael Shoemate Vikrant Singhal 87 2 0 19 Aug 2024
Better Locally Private Sparse Estimation Given Multiple Samples Per User Yuheng Ma Ke Jia Hanfang Yang FedML 85 1 0 08 Aug 2024
Private Heterogeneous Federated Learning Without a Trusted Server Revisited: Error-Optimal and Communication-Efficient Algorithms for Convex Losses Changyu Gao Andrew Lowy Xingyu Zhou Stephen J. Wright FedML 63 5 0 12 Jul 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 81 14 0 10 Jul 2024
Minimax And Adaptive Transfer Learning for Nonparametric Classification under Distributed Differential Privacy Constraints Arnab Auddy T. T. Cai Abhinav Chakraborty 95 1 0 28 Jun 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 101 14 0 20 Jun 2024
Optimal Federated Learning for Nonparametric Regression with Heterogeneous Distributed Differential Privacy Constraints T. T. Cai Abhinav Chakraborty Lasse Vuursteen FedML 83 3 0 10 Jun 2024
Federated Nonparametric Hypothesis Testing with Differential Privacy Constraints: Optimal Rates and Adaptive Tests T. T. Cai Abhinav Chakraborty Lasse Vuursteen FedML 77 2 0 10 Jun 2024
Learning with User-Level Local Differential Privacy Puning Zhao Li Shen Rongfei Fan Qingming Li Huiwen Wu Xiaogang Xu Zhe Liu 55 3 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 Xiaogang Xu Zhe Liu 79 7 0 22 May 2024
Online Learning with Unknown Constraints Karthik Sridharan Seung Won Wilson Yoo 63 2 0 06 Mar 2024
Defending Against Data Reconstruction Attacks in Federated Learning: An Information Theory Approach Qi Tan Qi Li Yi Zhao Zhuotao Liu Xiaobing Guo Ke Xu FedML 73 2 0 02 Mar 2024
Clients Collaborate: Flexible Differentially Private Federated Learning with Guaranteed Improvement of Utility-Privacy Trade-off Yuecheng Li Lele Fu Tong Wang Jian Lou Bin Chen Lei Yang Zibin Zheng Zibin Zheng Chuan Chen FedML 104 4 0 10 Feb 2024
Mean Estimation with User-Level Privacy for Spatio-Temporal IoT Datasets V. A. Rameshwar Anshoo Tandon Prajjwal Gupta Aditya Vikram Singh Novoneel Chakraborty Abhay Sharma 85 3 0 29 Jan 2024
User-level Differentially Private Stochastic Convex Optimization: Efficient Algorithms with Optimal Rates Hilal Asi Daogao Liu 69 11 0 07 Nov 2023
SoK: Memorization in General-Purpose Large Language Models Valentin Hartmann Anshuman Suri Vincent Bindschaedler David Evans Shruti Tople Robert West KELM LLMAG 89 24 0 24 Oct 2023
User Inference Attacks on Large Language Models Nikhil Kandpal Krishna Pillutla Alina Oprea Peter Kairouz Christopher A. Choquette-Choo Zheng Xu SILM AAML 132 19 0 13 Oct 2023
Better and Simpler Lower Bounds for Differentially Private Statistical Estimation Shyam Narayanan FedML 68 11 0 10 Oct 2023
User-Level Differential Privacy With Few Examples Per User Badih Ghazi Pritish Kamath Ravi Kumar Pasin Manurangsi Raghu Meka Chiyuan Zhang 89 12 0 21 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 92 18 0 11 Sep 2023
ULDP-FL: Federated Learning with Across Silo User-Level Differential Privacy Fumiyuki Kato Li Xiong Shun Takagi Yang Cao Masatoshi Yoshikawa FedML 69 4 0 23 Aug 2023
Mean Estimation with User-level Privacy under Data Heterogeneity Rachel Cummings Vitaly Feldman Audra McMillan Kunal Talwar FedML 71 27 0 28 Jul 2023
Randomized Quantization is All You Need for Differential Privacy in Federated Learning Yeojoon Youn Zihao Hu Juba Ziani Jacob D. Abernethy FedML 70 21 0 20 Jun 2023
Differentially Private Wireless Federated Learning Using Orthogonal Sequences Xizixiang Wei Tianhao Wang Ruiquan Huang Cong Shen Jing Yang H. Vincent Poor 95 1 0 14 Jun 2023
Federated Linear Contextual Bandits with User-level Differential Privacy Ruiquan Huang Huanyu Zhang Luca Melis Milan Shen Meisam Hajzinia J. Yang FedML 54 12 0 08 Jun 2023
Concentrated Geo-Privacy Yuting Liang K. Yi 51 6 0 31 May 2023
Training Data Extraction From Pre-trained Language Models: A Survey Shotaro Ishihara 118 48 0 25 May 2023
Learning across Data Owners with Joint Differential Privacy Yangsibo Huang Haotian Jiang Daogao Liu Mohammad Mahdian Jieming Mao Vahab Mirrokni FedML 72 0 0 25 May 2023
Post-processing Private Synthetic Data for Improving Utility on Selected Measures Hao Wang Shivchander Sudalairaj J. Henning Kristjan Greenewald Akash Srivastava 53 6 0 24 May 2023
On User-Level Private Convex Optimization Badih Ghazi Pritish Kamath Ravi Kumar Raghu Meka Pasin Manurangsi Chiyuan Zhang FedML 54 10 0 08 May 2023
A Polynomial Time, Pure Differentially Private Estimator for Binary Product Distributions Vikrant Singhal 91 9 0 13 Apr 2023
Subset-Based Instance Optimality in Private Estimation Travis Dick Alex Kulesza Ziteng Sun A. Suresh 101 9 0 01 Mar 2023
Personalized Privacy-Preserving Framework for Cross-Silo Federated Learning Van Tuan Tran Huy Hieu Pham Kok-Seng Wong FedML 85 8 0 22 Feb 2023
Multi-Message Shuffled Privacy in Federated Learning Antonious M. Girgis Suhas Diggavi FedML 95 9 0 22 Feb 2023
Multi-Task Differential Privacy Under Distribution Skew Walid Krichene Prateek Jain Shuang Song Mukund Sundararajan Abhradeep Thakurta Li Zhang FedML 61 3 0 15 Feb 2023
Continual Mean Estimation Under User-Level Privacy Anand George Lekshmi Ramesh A. V. Singh Himanshu Tyagi FedML 70 9 0 20 Dec 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 92 30 0 20 Nov 2022
Discrete Distribution Estimation under User-level Local Differential Privacy Jayadev Acharya Yuhan Liu Ziteng Sun 64 16 0 07 Nov 2022
Subspace Recovery from Heterogeneous Data with Non-isotropic Noise John C. Duchi Vitaly Feldman Lunjia Hu Kunal Talwar FedML 56 12 0 24 Oct 2022
Algorithms with More Granular Differential Privacy Guarantees Badih Ghazi Ravi Kumar Pasin Manurangsi Thomas Steinke 120 7 0 08 Sep 2022
A Generative Framework for Personalized Learning and Estimation: Theory, Algorithms, and Privacy Kaan Ozkara Antonious M. Girgis Deepesh Data Suhas Diggavi FedML 58 3 0 05 Jul 2022
On Privacy and Personalization in Cross-Silo Federated Learning Ziyu Liu Shengyuan Hu Zhiwei Steven Wu Virginia Smith FedML 106 56 0 16 Jun 2022
Subject Granular Differential Privacy in Federated Learning Virendra J. Marathe Pallika H. Kanani Daniel W. Peterson Guy Steele Jr FedML 56 9 0 07 Jun 2022