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One cite over still

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Oliver Kennedy 2020-12-20 18:54:40 -05:00
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circuits-model-runtime.tex
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@ -109,7 +109,7 @@ We now have all the pieces to argue that using our approximation algorithm, the
%
\[
O_k\left(\frac 1{\eps^2}\cdot\qruntime{Q,\db_{max}}\cdot \log{\frac{1}{\conf}}\cdot \log(n)\right)
\].
\]
\end{Corollary}
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\begin{proof}

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related-work.tex
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@ -29,7 +29,7 @@ Amarilli et al. investigated tractable classes of databases for more complex que
Another line of work, studies which structural properties of lineage formulas lead to tractable cases~\cite{kenig-13-nclexpdc,roy-11-f,sen-10-ronfqevpd}.
Several techniques for approximating tuple probabilities have been proposed in related work~\cite{FH13,heuvel-19-anappdsd,DBLP:conf/icde/OlteanuHK10,DS07}, relying on Monte Carlo sampling, e.g.,~\cite{DS07}, or a branch-and-bound paradigm~\cite{DBLP:conf/icde/OlteanuHK10}.
The approximation algorithm for bag expectation we present in this work is based on sampling.
Our approximation algorithm is also based on sampling.
Fink et al.~\cite{FH12} study aggregate queries over a probabilistic version of the extension of K-relations for aggregate queries proposed in~\cite{AD11d} (this data model is referred to as \emph{pvc-tables}). As an extension of K-relations, this approach supports bags. Probabilities are computed using a decomposition approach~\cite{DBLP:conf/icde/OlteanuHK10}. % over the symbolic expressions that are used as tuple annotations and values in pvc-tables.
% \cite{FH12} identifies a tractable class of queries involving aggregation.