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authorThibaut Horel <thibaut.horel@gmail.com>2013-02-11 19:02:57 -0800
committerThibaut Horel <thibaut.horel@gmail.com>2013-02-11 19:02:57 -0800
commitc7b0c48affdf7bb19417a4016ba2a871792fbca6 (patch)
tree4b349fa5e2809623e31f0fb560ea1ab4e41ed18f /main.tex
parentfb4e13e1d19a9efe792a2b8c52e9eb95e1b0807b (diff)
downloadrecommendation-c7b0c48affdf7bb19417a4016ba2a871792fbca6.tar.gz
Moving Chen's lemma
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@@ -17,21 +17,13 @@ element $i$ to be included is the one which maximizes the
\end{align}
This is repeated until the sum of costs of elements in $S$ reaches the budget
constraint $B$. Denote by $S_G$ the set constructed by this heuristic and let
-$i^*$ be the element of maximum value. Then, the following lemma holds:
-\begin{lemma}~\cite{chen}\label{lemma:greedy-bound}
-Let $S_G$ be the set computed by the greedy algorithm and let
-$i^* = \argmax_{i\in\mathcal{N}} V(\{i\}).$ We have:
-\begin{displaymath}
-OPT \leq \frac{e}{e-1}\big( 3 V(S_G) + 2 V(i^*)\big).
-\end{displaymath}
-\end{lemma}
-
-This lemma immediately implies that the following algorithm:
+$i^*=\argmax_{i\in\mathcal{N}} V(\{i\})$ be the element of maximum value. Then,
+the following algorithm:
\begin{equation}\label{eq:max-algorithm}
\textbf{if}\; V(\{i^*\}) \geq V(S_G)\; \textbf{return}\; \{i^*\}
\;\textbf{else return}\; S_G
\end{equation}
-has an approximation ratio of $\frac{5e}{e-1}$.
+has an approximation ratio of $\frac{5e}{e-1}$ \cite{chen}.
\subsection{Submodular Maximization in the Strategic Case}