Optimality of Non-Interactive Randomized Response
By Peter Kairouz, Sewoong Oh, Pramod Viswanath. 2014
11 citations recorded by the source corpus.
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Peter Kairouz
- Graham Cormode
- Sewoong Oh
- Pramod Viswanath
- Xiaokui Xiao
- Tejas D. Kulkarni
- Y. Yang
- Divesh Srivastava
Citations in the corpus
- Marginal Release Under Local Differential Privacy (2017, background): “There is a growing theoretical understanding of LDP. Kairouz et al. [23, 22] study how to estimate the frequency of a single categorical attribute, and propose optimal generalizations of randomized response.”
- Extremal Mechanisms for Local Differential Privacy (2014, methodology): “In addition, the techniques developed in this work can be generalized to find optimal privatization mechanisms in a setting where different individuals can collaborate interactively and each individual can be an analyst [23].”
- Collecting and Analyzing Data from Smart Device Users with Local Differential Privacy (2016, background): “Kairouz et al. [15] show that a version of randomized response is an optimal mechanism for frequency estimation on a single binary attribute.”
- Locally differentially-private distribution estimation (2016, background): “Although non-interactive mechanisms are provably optimal in certain setups [10], the tradeoff under study may in general benefit from more complex, interactive channel structures.”