Minimax Optimal Procedures for Locally Private Estimation

8 April 2016

Papers citing "Minimax Optimal Procedures for Locally Private Estimation"

50 / 69 papers shown

Title
Towards Trustworthy Federated Learning with Untrusted Participants Youssef Allouah R. Guerraoui John Stephan FedML 55 0 0 03 May 2025
Locally Private Nonparametric Contextual Multi-armed Bandits Yuheng Ma Feiyu Jiang Zifeng Zhao Hanfang Yang Y. Yu 44 0 0 11 Mar 2025
Distribution-Aware Mean Estimation under User-level Local Differential Privacy Corentin Pla Hugo Richard Maxime Vono FedML 39 0 0 12 Oct 2024
Camel: Communication-Efficient and Maliciously Secure Federated Learning in the Shuffle Model of Differential Privacy Shuangqing Xu Yifeng Zheng Zhongyun Hua FedML 21 2 0 04 Oct 2024
Better Locally Private Sparse Estimation Given Multiple Samples Per User Yuheng Ma Ke Jia Hanfang Yang FedML 36 1 0 08 Aug 2024
Contraction of Private Quantum Channels and Private Quantum Hypothesis Testing Theshani Nuradha Mark M. Wilde 39 6 0 26 Jun 2024
Beyond Statistical Estimation: Differentially Private Individual Computation via Shuffling Shaowei Wang Changyu Dong Xiangfu Song Jin Li Zhili Zhou Di Wang Han Wu 41 0 0 26 Jun 2024
Locally Private Estimation with Public Features Yuheng Ma Ke Jia Hanfang Yang 42 3 0 22 May 2024
Sketches-based join size estimation under local differential privacy Meifan Zhang Xin Liu Lihua Yin 26 0 0 19 May 2024
Smooth Sensitivity for Geo-Privacy Yuting Liang Ke Yi 30 0 0 10 May 2024
Private Online Community Detection for Censored Block Models Mohamed Seif Liyan Xie Andrea J. Goldsmith H. Vincent Poor 36 1 0 09 May 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 18 3 0 29 Jan 2024
General Inferential Limits Under Differential and Pufferfish Privacy J. Bailie Ruobin Gong 35 1 0 27 Jan 2024
Sample-Optimal Locally Private Hypothesis Selection and the Provable Benefits of Interactivity A. F. Pour Hassan Ashtiani S. Asoodeh 41 0 0 09 Dec 2023
Exact Optimality of Communication-Privacy-Utility Tradeoffs in Distributed Mean Estimation Berivan Isik Wei-Ning Chen Ayfer Özgür Tsachy Weissman Albert No 61 19 0 08 Jun 2023
Triangle Counting with Local Edge Differential Privacy T. Eden Quanquan C. Liu Sofya Raskhodnikova Adam D. Smith 72 13 0 03 May 2023
Mean Estimation Under Heterogeneous Privacy: Some Privacy Can Be Free Syomantak Chaudhuri T. Courtade 27 4 0 27 Apr 2023
Federated Privacy-preserving Collaborative Filtering for On-Device Next App Prediction A. Sayapin Gleb Balitskiy Daniel Bershatsky Aleksandr Katrutsa Evgeny Frolov Alexey Frolov Ivan Oseledets Vitaliy N. Kharin FedML 26 1 0 05 Feb 2023
General Gaussian Noise Mechanisms and Their Optimality for Unbiased Mean Estimation Aleksandar Nikolov Haohua Tang 49 4 0 31 Jan 2023
Anonymized Histograms in Intermediate Privacy Models Badih Ghazi Pritish Kamath Ravi Kumar Pasin Manurangsi PICV 115 1 0 27 Oct 2022
Contraction of Locally Differentially Private Mechanisms S. Asoodeh Huanyu Zhang 26 10 0 24 Oct 2022
On the Impossible Safety of Large AI Models El-Mahdi El-Mhamdi Sadegh Farhadkhani R. Guerraoui Nirupam Gupta L. Hoang Rafael Pinot Sébastien Rouault John Stephan 30 31 0 30 Sep 2022
Privacy Aware Experimentation over Sensitive Groups: A General Chi Square Approach R. Friedberg Ryan M. Rogers 26 3 0 17 Aug 2022
Differentially Private Linear Bandits with Partial Distributed Feedback Fengjiao Li Xingyu Zhou Bo Ji FedML 34 13 0 12 Jul 2022
sqSGD: Locally Private and Communication Efficient Federated Learning Yan Feng Tao Xiong Ruofan Wu Lingjuan Lv Leilei Shi FedML 25 2 0 21 Jun 2022
Communication-constrained hypothesis testing: Optimality, robustness, and reverse data processing inequalities Ankit Pensia Varun Jog Po-Ling Loh 23 8 0 06 Jun 2022
Fine-grained Poisoning Attack to Local Differential Privacy Protocols for Mean and Variance Estimation Xiaoguang Li Ninghui Li Wenhai Sun Neil Zhenqiang Gong Hui Li AAML 63 15 0 24 May 2022
Network change point localisation under local differential privacy Mengchu Li Thomas B. Berrett Yi Yu 27 7 0 14 May 2022
Statistical Data Privacy: A Song of Privacy and Utility Aleksandra B. Slavkovic Jeremy Seeman 23 26 0 06 May 2022
Optimal Algorithms for Mean Estimation under Local Differential Privacy Hilal Asi Vitaly Feldman Kunal Talwar 40 41 0 05 May 2022
OPTT: Optimal Piecewise Transformation Technique for Analyzing Numerical Data under Local Differential Privacy Fei Ma Renbo Zhu Ping Wang 21 1 0 09 Dec 2021
Differentially Private Federated Learning on Heterogeneous Data Maxence Noble A. Bellet Aymeric Dieuleveut FedML 13 102 0 17 Nov 2021
Distribution-Invariant Differential Privacy Xuan Bi Xiaotong Shen 18 13 0 08 Nov 2021
Improving the utility of locally differentially private protocols for longitudinal and multidimensional frequency estimates Héber H. Arcolezi Jean-François Couchot Bechara al Bouna X. Xiao 15 29 0 08 Nov 2021
Locally Differentially Private Reinforcement Learning for Linear Mixture Markov Decision Processes Chonghua Liao Jiafan He Quanquan Gu 6 17 0 19 Oct 2021
Private sampling: a noiseless approach for generating differentially private synthetic data M. Boedihardjo Thomas Strohmer Roman Vershynin SyDa 29 14 0 30 Sep 2021
Private Adaptive Gradient Methods for Convex Optimization Hilal Asi John C. Duchi Alireza Fallah O. Javidbakht Kunal Talwar 16 53 0 25 Jun 2021
Shuffle Private Stochastic Convex Optimization Albert Cheu Matthew Joseph Jieming Mao Binghui Peng FedML 31 25 0 17 Jun 2021
Differentially private inference via noisy optimization Marco Avella-Medina Casey Bradshaw Po-Ling Loh FedML 40 29 0 19 Mar 2021
Deep Learning with Label Differential Privacy Badih Ghazi Noah Golowich Ravi Kumar Pasin Manurangsi Chiyuan Zhang 42 144 0 11 Feb 2021
Optimal Private Median Estimation under Minimal Distributional Assumptions Christos Tzamos Emmanouil-Vasileios Vlatakis-Gkaragkounis Ilias Zadik 27 21 0 12 Nov 2020
The Cost of Privacy in Generalized Linear Models: Algorithms and Minimax Lower Bounds T. Tony Cai Yichen Wang Linjun Zhang FedML 43 20 0 08 Nov 2020
Unified lower bounds for interactive high-dimensional estimation under information constraints Jayadev Acharya C. Canonne Ziteng Sun Himanshu Tyagi 28 29 0 13 Oct 2020
An Information Theoretic approach to Post Randomization Methods under Differential Privacy Fadhel Ayed Marco Battiston F. Camerlenghi 24 2 0 23 Sep 2020
Interactive Inference under Information Constraints Jayadev Acharya C. Canonne Yuhan Liu Ziteng Sun Himanshu Tyagi 28 35 0 21 Jul 2020
Evading Curse of Dimensionality in Unconstrained Private GLMs via Private Gradient Descent Shuang Song Thomas Steinke Om Thakkar Abhradeep Thakurta 27 50 0 11 Jun 2020
Locally private non-asymptotic testing of discrete distributions is faster using interactive mechanisms Thomas B. Berrett C. Butucea 27 34 0 26 May 2020
Local Differential Privacy based Federated Learning for Internet of Things Yang Zhao Jun Zhao Mengmeng Yang Teng Wang Ning Wang Lingjuan Lyu Dusit Niyato Kwok-Yan Lam 25 292 0 19 Apr 2020
Asymptotic Theory for Differentially Private Generalized $β$ -models with Parameters Increasing Yifan Fan Huiming Zhang T. Yan FedML 12 14 0 28 Feb 2020
BiSample: Bidirectional Sampling for Handling Missing Data with Local Differential Privacy Lin Sun Xiaojun Ye Jun Zhao Chenhui Lu Mengmeng Yang 17 8 0 13 Feb 2020