From a9eb124b9a326104326723e9693ae4779c4df25b Mon Sep 17 00:00:00 2001
From: Stratis Ioannidis <stratis@stratis-Latitude-E6320.(none)>
Date: Mon, 11 Feb 2013 20:45:44 -0800
Subject: edits

---
 problem.tex | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

(limited to 'problem.tex')

diff --git a/problem.tex b/problem.tex
index 358c825..9d67074 100644
--- a/problem.tex
+++ b/problem.tex
@@ -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
-- 
cgit v1.2.3-70-g09d2

