Differentially Private Hierarchical Group Size Estimation
By Yu-Hsuan Kuo, Cho-Chun Chiu, Daniel Kifer, Michael Hay, Ashwin Machanavajjhala. 2018
4 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.
- Matthew Joseph
- Zhiwei Steven Wu
- Jieming Mao
- Janardhan Kulkarni
- S. Gopi
- Sergey Yekhanin
- P. Gulhane
- Judy Hanwen Shen
Citations in the corpus
- An Economic Analysis of Privacy Protection and Statistical Accuracy as Social Choices (2018, neutral): “The matrix mechanism is also under active development for use by the Census Bureau (McKenna et al. 2018; Kuo et al. 2018).”
- Locally Private Gaussian Estimation (2018, background): “Since its introduction [14], a rich line of work has made differential privacy a compelling privacy guarantee (see Dwork et al. [15] and Vadhan [26] for surveys), and deployments of differential privacy now exist at many organizations, including Apple [2], Google [5, 16], Microsoft [11], Mozilla [3]”
- Differentially Private Set Union (2020, background): “Differential privacy is deployed in many industries, including Apple (Apple, 2017), Google (Erlingsson et al., 2014; Bittau et al., 2017), Microsoft (Ding et al., 2017), Mozilla (Avent et al., 2017), and the US Census Bureau (Abowd, 2016; Kuo et al., 2018).”