Optimal Differential Privacy Composition for Exponential Mechanisms and the Cost of Adaptivity

30 September 2019

Papers citing "Optimal Differential Privacy Composition for Exponential Mechanisms and the Cost of Adaptivity"

8 / 8 papers shown

Title
Practical Differentially Private Top- $k$ Selection with Pay-what-you-get Composition D. Durfee Ryan M. Rogers 50 87 0 10 May 2019
The Role of Interactivity in Local Differential Privacy Matthew Joseph Jieming Mao Seth Neel Aaron Roth 59 65 0 07 Apr 2019
Lower Bounds for Locally Private Estimation via Communication Complexity John C. Duchi Ryan M. Rogers 51 93 0 01 Feb 2019
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 196 6,113 0 01 Jul 2016
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
Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds Mark Bun Thomas Steinke 84 831 0 06 May 2016
The Composition Theorem for Differential Privacy Peter Kairouz Sewoong Oh Pramod Viswanath 107 681 0 04 Nov 2013
What Can We Learn Privately? S. Kasiviswanathan Homin K. Lee Kobbi Nissim Sofya Raskhodnikova Adam D. Smith 126 1,465 0 06 Mar 2008