1 citations · 1 across the 1 of their papers we have counts for
2 papers
cs.CR2019★ 1 cited
Interpreting Epsilon of Differential Privacy in Terms of Advantage in Guessing or Approximating Sensitive Attributes
Peeter Laud, Alisa Pankova
There are numerous methods of achieving -differential privacy (DP). The question is what is the appropriate value of , since there is no common agreement on a "sufficiently s…
cs.CR2018
Achieving Differential Privacy using Methods from Calculus
Peeter Laud, Alisa Pankova, Martin Pettai
We introduce derivative sensitivity, an analogue to local sensitivity for continuous functions. We use this notion in an analysis that determines the amount of noise to be added to…