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text: Minor corrections

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Manos Katsomallos
2021-10-19 03:43:57 +02:00
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text/preliminaries/privacy.tex
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@ -383,7 +383,7 @@ In the special case that we query disjoint data sets, we can take advantage of t
When $m \in \mathbb{Z}^+$ independent privacy mechanisms, satisfying $\varepsilon_1$-, $\varepsilon_2$-,\dots, $\varepsilon_m$-differential privacy respectively, are applied over disjoint independent subsets of a data set, they provide a privacy guarantee equal to $\max_{i \in [1, m]} \varepsilon_i$.
\end{theorem}
When the users consider recent data releases more privacy sensitive than distant ones, we estimate the overall privacy loss in a time fading manner according to a temporal discounting function, e.g.,~exponential, hyperbolic,~\cite{farokhi2020temporally}.
When the users consider recent data releases more privacy-sensitive than distant ones, we estimate the overall privacy loss in a time fading manner according to a temporal discounting function, e.g.,~exponential, hyperbolic,~\cite{farokhi2020temporally}.
\begin{theorem}
[Sequential composition with temporal discounting]