problem: OCD
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		@ -80,7 +80,7 @@ Theorem~\ref{theor:thething-prv} states how to achieve the desired privacy goal
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\begin{theorem}
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  [{\Thething} privacy]
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  \label{theor:thething-prv}
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  Let $\mathcal{M}$ be a mechanism with input a time series $S_T$, where $T$ is the set of the  involved timestamps, and $L \subseteq T$ be the set of {\thething}  timestamps.
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  Let $\mathcal{M}$ be a mechanism with input a time series $S_T$, where $T$ is the set of the  involved timestamps, and $L \subseteq T$ be the set of {\thething} timestamps.
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  $\mathcal{M}$ is decomposed to $\varepsilon$-differential private sub-mechanisms $\mathcal{M}_t$, for every $t \in T$, which apply independent randomness to the event at $t$.
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  Then, given a privacy budget $\varepsilon$, $\mathcal{M}$ satisfies {\thething} privacy if for any $t$ it holds that
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  $$ \sum_{i\in L \cup \{t\}} \varepsilon_i \leq \varepsilon$$
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