Collecting Telemetry Data Privately

5 December 2017

Papers citing "Collecting Telemetry Data Privately"

50 / 346 papers shown

Title
Testing Differential Privacy with Dual Interpreters Hengchu Zhang Edo Roth Andreas Haeberlen B. Pierce Aaron Roth 61 16 0 08 Oct 2020
Privacy Enhancement via Dummy Points in the Shuffle Model Xiaochen Li Weiran Liu Hanwen Feng Kunzhe Huang Jinfei Liu K. Ren Zhan Qin FedML 93 4 0 29 Sep 2020
Privacy-Preserving Dynamic Personalized Pricing with Demand Learning Xi Chen D. Simchi-Levi Yining Wang 133 62 0 27 Sep 2020
On Distributed Differential Privacy and Counting Distinct Elements Lijie Chen Badih Ghazi Ravi Kumar Pasin Manurangsi FedML 103 31 0 21 Sep 2020
Answering Multi-Dimensional Range Queries under Local Differential Privacy Jianyu Yang Tianhao Wang Ninghui Li Xiang Cheng Sen Su 56 37 0 14 Sep 2020
Strengthening Order Preserving Encryption with Differential Privacy Amrita Roy Chowdhury Bolin Ding S. Jha Weiran Liu Jingren Zhou 45 9 0 11 Sep 2020
Multi-Central Differential Privacy Thomas Steinke 47 8 0 11 Sep 2020
A Framework for Private Matrix Analysis Jalaj Upadhyay Sarvagya Upadhyay 69 4 0 06 Sep 2020
Differentially Private Clustering: Tight Approximation Ratios Badih Ghazi Ravi Kumar Pasin Manurangsi 78 54 0 18 Aug 2020
Local Differential Privacy and Its Applications: A Comprehensive Survey Mengmeng Yang Lingjuan Lyu Jun Zhao Tianqing Zhu Kwok-Yan Lam 89 146 0 09 Aug 2020
Verifying Pufferfish Privacy in Hidden Markov Models Depeng Liu Bow-Yaw Wang Lijun Zhang 15 2 0 04 Aug 2020
Private Post-GAN Boosting Marcel Neunhoeffer Zhiwei Steven Wu Cynthia Dwork 196 29 0 23 Jul 2020
Privacy Amplification via Random Check-Ins Borja Balle Peter Kairouz H. B. McMahan Om Thakkar Abhradeep Thakurta FedML 87 72 0 13 Jul 2020
Understanding Unintended Memorization in Federated Learning Om Thakkar Swaroop Indra Ramaswamy Rajiv Mathews Franccoise Beaufays FedML 83 47 0 12 Jun 2020
An Accurate, Scalable and Verifiable Protocol for Federated Differentially Private Averaging C. Sabater A. Bellet J. Ramon FedML 70 20 0 12 Jun 2020
CoinPress: Practical Private Mean and Covariance Estimation Sourav Biswas Yihe Dong Gautam Kamath Jonathan R. Ullman 84 117 0 11 Jun 2020
LDP-Fed: Federated Learning with Local Differential Privacy Stacey Truex Ling Liu Ka-Ho Chow Mehmet Emre Gursoy Wenqi Wei FedML 69 396 0 05 Jun 2020
Cheetah: Optimizing and Accelerating Homomorphic Encryption for Private Inference Brandon Reagen Wooseok Choi Yeongil Ko Vincent T. Lee Gu-Yeon Wei Hsien-Hsin S. Lee David Brooks 46 16 0 31 May 2020
Meta Clustering for Collaborative Learning Chenglong Ye R. Ghanadan Jie Ding 106 4 0 29 May 2020
DP-Cryptography: Marrying Differential Privacy and Cryptography in Emerging Applications Sameer Wagh Xi He Ashwin Machanavajjhala Prateek Mittal 93 22 0 19 Apr 2020
Differentially Private Assouad, Fano, and Le Cam Jayadev Acharya Ziteng Sun Huanyu Zhang FedML 81 60 0 14 Apr 2020
Can Two Walk Together: Privacy Enhancing Methods and Preventing Tracking of Users M. Naor Neil Vexler FedML 64 7 0 06 Apr 2020
Towards Effective Differential Privacy Communication for Users' Data Sharing Decision and Comprehension Aiping Xiong Tianhao Wang Ninghui Li S. Jha 57 62 0 31 Mar 2020
Sharp Composition Bounds for Gaussian Differential Privacy via Edgeworth Expansion Qinqing Zheng Jinshuo Dong Qi Long Weijie J. Su FedML 60 23 0 10 Mar 2020
Practical Privacy Preserving POI Recommendation Chaochao Chen Jun Zhou Bingzhe Wu W. Fang Li Wang Yuan Qi Xiaolin Zheng 70 68 0 05 Mar 2020
PAPRIKA: Private Online False Discovery Rate Control Wanrong Zhang Gautam Kamath Rachel Cummings 48 6 0 27 Feb 2020
Differentially Private Set Union Sivakanth Gopi P. Gulhane Janardhan Kulkarni J. Shen Milad Shokouhi Sergey Yekhanin FedML 42 32 0 22 Feb 2020
Privately Learning Markov Random Fields Huanyu Zhang Gautam Kamath Janardhan Kulkarni Zhiwei Steven Wu 77 25 0 21 Feb 2020
Private Mean Estimation of Heavy-Tailed Distributions Gautam Kamath Vikrant Singhal Jonathan R. Ullman 90 99 0 21 Feb 2020
Locally Private Hypothesis Selection Sivakanth Gopi Gautam Kamath Janardhan Kulkarni Aleksandar Nikolov Zhiwei Steven Wu Huanyu Zhang 78 27 0 21 Feb 2020
Differential Privacy for Eye Tracking with Temporal Correlations Efe Bozkir Onur Gunlu Wolfgang Fuhl Rafael F. Schaefer Enkelejda Kasneci 76 64 0 20 Feb 2020
LinkedIn's Audience Engagements API: A Privacy Preserving Data Analytics System at Scale Ryan M. Rogers S. Subramaniam Sean Peng D. Durfee Seunghyun Lee Santosh Kumar Kancha Shraddha Sahay P. Ahammad 54 81 0 14 Feb 2020
BiSample: Bidirectional Sampling for Handling Missing Data with Local Differential Privacy Lin Sun Xiaojun Ye Jun Zhao Chenhui Lu Mengmeng Yang 59 8 0 13 Feb 2020
Wireless Federated Learning with Local Differential Privacy Mohamed Seif Ravi Tandon Ming Li 121 171 0 12 Feb 2020
Privacy-Preserving Image Classification in the Local Setting Sen Wang J.Morris Chang 26 8 0 09 Feb 2020
Privacy-Preserving Boosting in the Local Setting Sen Wang J.Morris Chang FedML 50 3 0 06 Feb 2020
Pure Differentially Private Summation from Anonymous Messages Badih Ghazi Noah Golowich Ravi Kumar Pasin Manurangsi Rasmus Pagh A. Velingker FedML 120 46 0 05 Feb 2020
A workload-adaptive mechanism for linear queries under local differential privacy Ryan McKenna R. Maity A. Mazumdar G. Miklau 15 10 0 05 Feb 2020
Locally Private Distributed Reinforcement Learning Hajime Ono Tsubasa Takahashi OffRL 61 23 0 31 Jan 2020
A Blockchain-Based Approach for Saving and Tracking Differential-Privacy Cost Yang Zhao Jun Zhao Jiawen Kang Zehang Zhang Dusit Niyato Shuyu Shi 72 24 0 25 Jan 2020
Differentially Private and Fair Classification via Calibrated Functional Mechanism Jiahao Ding Xinyue Zhang Xiaohuan Li Junyi Wang Rong Yu Miao Pan FaML 74 39 0 14 Jan 2020
The power of synergy in differential privacy: Combining a small curator with local randomizers A. Beimel Aleksandra Korolova Kobbi Nissim Or Sheffet Uri Stemmer 68 15 0 18 Dec 2019
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 287 6,315 0 10 Dec 2019
Estimating Numerical Distributions under Local Differential Privacy Zitao Li Tianhao Wang Milan Lopuhaä-Zwakenberg B. Škorić Ninghui Li 58 92 0 02 Dec 2019
PCKV: Locally Differentially Private Correlated Key-Value Data Collection with Optimized Utility Xiaolan Gu Ming Li Yueqiang Cheng Li Xiong Yang Cao 66 82 0 28 Nov 2019
Deep Learning with Gaussian Differential Privacy Zhiqi Bu Jinshuo Dong Qi Long Weijie J. Su FedML 74 209 0 26 Nov 2019
Gradient Perturbation is Underrated for Differentially Private Convex Optimization Da Yu Huishuai Zhang Kwei-Herng Lai Yuening Li Helen Zhou 78 37 0 26 Nov 2019
Improving Frequency Estimation under Local Differential Privacy Milan Lopuhaä-Zwakenberg Zitao Li B. Škorić Ninghui Li 33 1 0 24 Nov 2019
Interaction is necessary for distributed learning with privacy or communication constraints Y. Dagan Vitaly Feldman 60 12 0 11 Nov 2019
Secure Federated Submodel Learning Chaoyue Niu Fan Wu Shaojie Tang Lifeng Hua Rongfei Jia Chengfei Lv Zhihua Wu Guihai Chen FedML 69 30 0 06 Nov 2019