A new data structure samples any entry of the noise vector in constant time while exactly reproducing the binary tree Gaussian mechanism distribution, applied to DP CountSketches for improved range counting and join size estimation.
In: Bansal, N., Nagarajan, V
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 2verdicts
UNVERDICTED 2roles
background 1polarities
background 1representative citing papers
A technique for enforcing differential privacy in temporal runtime monitoring by analyzing dependencies and injecting noise into specifications while using tree mechanisms to limit accuracy loss.
citing papers explorer
-
A Fast Gaussian Mechanism under Continual Observation, with Applications
A new data structure samples any entry of the noise vector in constant time while exactly reproducing the binary tree Gaussian mechanism distribution, applied to DP CountSketches for improved range counting and join size estimation.
-
Differentially Private Runtime Monitoring
A technique for enforcing differential privacy in temporal runtime monitoring by analyzing dependencies and injecting noise into specifications while using tree mechanisms to limit accuracy loss.