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authorStratis Ioannidis <stratis@stratis-Latitude-E6320.(none)>2013-02-11 20:45:44 -0800
committerStratis Ioannidis <stratis@stratis-Latitude-E6320.(none)>2013-02-11 20:45:44 -0800
commita9eb124b9a326104326723e9693ae4779c4df25b (patch)
tree10c960337e020ce91762d39c1a7a529cf4db1f67 /problem.tex
parent05072094652d9587c22364d50ab8f004479ca900 (diff)
downloadrecommendation-EC.tar.gz
editsEC
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@@ -184,8 +184,8 @@ Given that the full information problem \EDP{} is NP-hard, we further seek mecha
% The approximation ratio captures the \emph{price of truthfulness}, \emph{i.e.}, the relative value loss incurred by adding the truthfulness constraint. % to the value function maximization.
We stress here that the approximation ratio is defined with respect \emph{to the maximal value in the full information case}.
\item \emph{Computational Efficiency.} The allocation and payment function
- should be computable in polynomial time in the number of
- agents $n$. %\thibaut{Should we say something about the black-box model for $V$? Needed to say something in general, but not in our case where the value function can be computed in polynomial time}.
+ should be computable in time polynomial in various parameters.
+ %time in the number of agents $n$. %\thibaut{Should we say something about the black-box model for $V$? Needed to say something in general, but not in our case where the value function can be computed in polynomial time}.
\end{itemize}
As noted in \cite{singer-mechanisms, chen}, budget feasible reverse auctions are \emph{single parameter} auctions: each agent has only one