eng
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Leibniz International Proceedings in Informatics
1868-8969
2019-07-04
73:1
73:12
10.4230/LIPIcs.ICALP.2019.73
article
Scalable and Jointly Differentially Private Packing
Huang, Zhiyi
1
Zhu, Xue
1
The University of Hong Kong
We introduce an (epsilon, delta)-jointly differentially private algorithm for packing problems. Our algorithm not only achieves the optimal trade-off between the privacy parameter epsilon and the minimum supply requirement (up to logarithmic factors), but is also scalable in the sense that the running time is linear in the number of agents n. Previous algorithms either run in cubic time in n, or require a minimum supply per resource that is sqrt{n} times larger than the best possible.
https://drops.dagstuhl.de/storage/00lipics/lipics-vol132-icalp2019/LIPIcs.ICALP.2019.73/LIPIcs.ICALP.2019.73.pdf
Joint differential privacy
packing
scalable algorithms