The Role of Interactivity in Local Differential Privacy

7 April 2019

Papers citing "The Role of Interactivity in Local Differential Privacy"

22 / 22 papers shown

Title
Exponential Separations in Local Differential Privacy Matthew Joseph Jieming Mao Aaron Roth 36 11 0 01 Jul 2019
The Privacy Blanket of the Shuffle Model Borja Balle James Bell Adria Gascon Kobbi Nissim FedML 61 238 0 07 Mar 2019
Lower Bounds for Locally Private Estimation via Communication Complexity John C. Duchi Ryan M. Rogers 51 93 0 01 Feb 2019
Inference under Information Constraints I: Lower Bounds from Chi-Square Contraction Jayadev Acharya C. Canonne Himanshu Tyagi 72 110 0 30 Dec 2018
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 174 427 0 29 Nov 2018
The Structure of Optimal Private Tests for Simple Hypotheses C. Canonne Gautam Kamath Audra McMillan Adam D. Smith Jonathan R. Ullman 46 75 0 27 Nov 2018
Locally Private Gaussian Estimation Matthew Joseph Janardhan Kulkarni Jieming Mao Zhiwei Steven Wu FedML 74 38 0 20 Nov 2018
How to Use Heuristics for Differential Privacy Seth Neel Aaron Roth Zhiwei Steven Wu 46 26 0 19 Nov 2018
Test without Trust: Optimal Locally Private Distribution Testing Jayadev Acharya C. Canonne Cody R. Freitag Himanshu Tyagi 56 59 0 07 Aug 2018
Distributed Differential Privacy via Shuffling Albert Cheu Adam D. Smith Jonathan R. Ullman David Zeber M. Zhilyaev FedML 85 352 0 04 Aug 2018
Local Differential Privacy for Evolving Data Matthew Joseph Aaron Roth Jonathan R. Ullman Bo Waggoner 79 87 0 20 Feb 2018
Tight Lower Bounds for Locally Differentially Private Selection Jonathan R. Ullman 64 33 0 07 Feb 2018
Collecting Telemetry Data Privately Bolin Ding Janardhan Kulkarni Sergey Yekhanin 48 686 0 05 Dec 2017
Prochlo: Strong Privacy for Analytics in the Crowd Andrea Bittau Ulfar Erlingsson Petros Maniatis Ilya Mironov A. Raghunathan David Lie Mitch Rudominer Ushasree Kode J. Tinnés B. Seefeld 122 278 0 02 Oct 2017
Privacy Odometers and Filters: Pay-as-you-Go Composition Ryan M. Rogers Aaron Roth Jonathan R. Ullman Salil P. Vadhan 53 109 0 26 May 2016
Minimax Optimal Procedures for Locally Private Estimation John C. Duchi Martin J. Wainwright Michael I. Jordan 68 435 0 08 Apr 2016
Adaptive Learning with Robust Generalization Guarantees Rachel Cummings Katrina Ligett Kobbi Nissim Aaron Roth Zhiwei Steven Wu FedML 43 57 0 24 Feb 2016
Communication Lower Bounds for Statistical Estimation Problems via a Distributed Data Processing Inequality M. Braverman A. Garg Tengyu Ma Huy Le Nguyen David P. Woodruff FedML 50 175 0 24 Jun 2015
Local, Private, Efficient Protocols for Succinct Histograms Raef Bassily Adam D. Smith FedML 56 457 0 18 Apr 2015
RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response Ulfar Erlingsson Vasyl Pihur Aleksandra Korolova 92 1,990 0 25 Jul 2014
On Communication Cost of Distributed Statistical Estimation and Dimensionality A. Garg Tengyu Ma Huy Le Nguyen 73 102 0 07 May 2014
What Can We Learn Privately? S. Kasiviswanathan Homin K. Lee Kobbi Nissim Sofya Raskhodnikova Adam D. Smith 126 1,465 0 06 Mar 2008