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-rw-r--r--appendix.tex4
-rw-r--r--counterexample.tex2
-rw-r--r--main.tex2
-rw-r--r--notes.bib42
-rw-r--r--paper.tex2
-rw-r--r--proof_of_lower_bound1.tex2
6 files changed, 19 insertions, 35 deletions
diff --git a/appendix.tex b/appendix.tex
index 9175e34..6be1a85 100644
--- a/appendix.tex
+++ b/appendix.tex
@@ -641,7 +641,7 @@ The complexity of the mechanism is given by the following lemma.
The value function $V$ in \eqref{modified} can be computed in time
$O(\text{poly}(n, d))$ and the mechanism only involves a linear
number of queries to the function $V$.
- By Proposition~\ref{prop:monotonicity}, line 3 of Algorithm~\ref{mechanism}
+ By Proposition~\ref{prop:monotonicity}, line \ref{relaxexec} of Algorithm~\ref{mechanism}
can be computed in time
$O(\text{poly}(n, d, \log\log \frac{B}{b\varepsilon\delta}))$. Hence the allocation
function's complexity is as stated.
@@ -732,7 +732,7 @@ of Theorem~\ref{thm:main}.\hspace*{\stretch{1}}\qed
\section{Proof of Theorem \ref{thm:lowerbound}}\label{proofoflowerbound}
-Suppose, for contradiction, that such a mechanism exists. Consider two
+Suppose, for contradiction, that such a mechanism exists. From Myerson's Theorem \cite{myerson}, a single parameter auction is truthful if and only if the allocation function is monotone and agents are paid theshold payments. Consider two
experiments with dimension $d=2$, such that $x_1 = e_1=[1 ,0]$, $x_2=e_2=[0,1]$
and $c_1=c_2=B/2+\epsilon$. Then, one of the two experiments, say, $x_1$, must
be in the set selected by the mechanism, otherwise the ratio is unbounded,
diff --git a/counterexample.tex b/counterexample.tex
index 896d672..6e21de5 100644
--- a/counterexample.tex
+++ b/counterexample.tex
@@ -59,4 +59,4 @@ Hence, the greedy solution will be $\{x_3, x_4\}$ with value:
As a consequence the mechanism will allocate to user $1$ in this case. By
reducing her cost, user 3, who was previously allocated, is now rejected by the
mechanism. This contradicts the monotonicity of the allocation rule, hence its
-truthfulness by Myerson's theorem \cite{myerson}.
+truthfulness by Myerson's theorem \cite{myerson}, which states that a single parameter auction is truthful if and only if the allocation function is monotone and agents are paid theshold payments.
diff --git a/main.tex b/main.tex
index 324f11f..b6031cb 100644
--- a/main.tex
+++ b/main.tex
@@ -65,7 +65,7 @@ fixed costs $c_{-i}$ of agents in $\mathcal{N}\setminus\{i\}$, $i\in S(c_i,
c_{-i})$ implies $i\in S(c_i', c_{-i})$, and (b)
agents are paid \emph{threshold payments}, \emph{i.e.}, for all $i\in S(c)$, $p_i(c)=\inf\{c_i': i\in S(c_i', c_{-i})\}$.
\end{lemma}
-Lemma~\ref{thm:myerson-variant} allow us to incorporate our relaxation in the above framework, yielding the following theorem:
+Lemma~\ref{thm:myerson-variant} allows us to incorporate our relaxation in the above framework, yielding the following theorem:
\begin{theorem}\label{thm:main}
For any $\delta>0$, and any $\epsilon>0$, there exists a $\delta$-truthful, individually rational
and budget feasible mechanim for \EDP{} that runs in time
diff --git a/notes.bib b/notes.bib
index 61affef..0b66d8b 100644
--- a/notes.bib
+++ b/notes.bib
@@ -8,10 +8,8 @@
@inproceedings{dughmi2011convex,
title={From convex optimization to randomized mechanisms: toward optimal combinatorial auctions},
author={Dughmi, Shaddin and Roughgarden, Tim and Yan, Qiqi},
- booktitle={Proceedings of the 43rd annual ACM symposium on Theory of computing},
- pages={149--158},
- year={2011},
- organization={ACM}
+ booktitle={STOC},
+ year={2011}
}
@@ -50,13 +48,14 @@ year = 2012
year = {2011}
}
-@unpublished{kearns2012,
+@misc{kearns2012,
author = {Michael Kearns and
Mallesh M. Pai and
Aaron Roth and
Jonathan Ullman},
- title = {Mechanism Design in Large Games: Incentives and Privacy},
- year = {2012}
+ title = {Private Equilibrium Release, Large Games, and No-Regret Learning},
+ year = {2012},
+ note = {\url{http://arxiv.org/abs/1207.4084v1}}
}
@article{pai2013privacy,
@@ -397,11 +396,7 @@ year = 2012
title = {How to win friends and influence people, truthfully: influence
maximization mechanisms for social networks},
booktitle = {WSDM},
- year = {2012},
- pages = {733-742},
- ee = {http://doi.acm.org/10.1145/2124295.2124381},
- crossref = {DBLP:conf/wsdm/2012},
- bibsource = {DBLP, http://dblp.uni-trier.de}
+ year = {2012}
}
@proceedings{DBLP:conf/wsdm/2012,
@@ -423,11 +418,7 @@ year = 2012
author = {Yaron Singer},
title = {Budget Feasible Mechanisms},
booktitle = {FOCS},
- year = {2010},
- pages = {765-774},
- ee = {http://doi.ieeecomputersociety.org/10.1109/FOCS.2010.78},
- crossref = {DBLP:conf/focs/2010},
- bibsource = {DBLP, http://dblp.uni-trier.de}
+ year = {2010}
}
@proceedings{DBLP:conf/focs/2010,
@@ -581,11 +572,7 @@ year = 2012
title = {Near-optimal Nonmyopic Value of Information in Graphical
Models},
booktitle = {UAI},
- year = {2005},
- pages = {324-331},
- ee = {http://uai.sis.pitt.edu/displayArticleDetails.jsp?mmnu=1{\&}smnu=2{\&}article_id=1238{\&}proceeding_id=21},
- crossref = {DBLP:conf/uai/2005},
- bibsource = {DBLP, http://dblp.uni-trier.de}
+ year = {2005}
}
@proceedings{DBLP:conf/uai/2005,
@@ -668,10 +655,8 @@ year = "2013"
@inproceedings{singerposted,
author = {Badanidiyuru, Ashwinkumar and Kleinberg, Robert and Singer, Yaron},
title = {Learning on a budget: posted price mechanisms for online procurement},
- booktitle = {Proceedings of the 13th ACM Conference on Electronic Commerce},
- series = {EC '12},
- year = {2012},
- pages = {128--145},
+ booktitle = {EC},
+ year = {2012}
}
@article{sylvester,
@@ -701,10 +686,9 @@ author = "Alkiviadis G. Akritas and Evgenia K. Akritas and Genadii I. Malaschono
@inproceedings{dughmi-truthful,
title = {A truthful randomized mechanism for combinatorial public projects via convex optimization},
- booktitle = {Proceedings of the 12th {ACM} conference on Electronic commerce},
+ booktitle = {EC},
author = {Dughmi, Shaddin},
- year = {2011},
- pages = {263–272},
+ year = {2011}
}
@article{lavi-truthful,
diff --git a/paper.tex b/paper.tex
index bd2b693..1fab52e 100644
--- a/paper.tex
+++ b/paper.tex
@@ -35,7 +35,7 @@
\input{approximation}
\section{Mechanism for \SEDP{}}\label{sec:mechanism}
\input{main}
-\section{Conclusion}
+\section{Conclusions}
\input{conclusion}
\bibliographystyle{abbrvnat}
\bibliography{notes}
diff --git a/proof_of_lower_bound1.tex b/proof_of_lower_bound1.tex
index b665a50..b1a7c67 100644
--- a/proof_of_lower_bound1.tex
+++ b/proof_of_lower_bound1.tex
@@ -1 +1 @@
-Given $M>1$, consider $n=4$ experiments of dimension $d=2$. For $e_1,e_2$ the standard basis vectors in $\reals^2$, let $x_1 = e_1$, $x_2 = e_1$, and $x_3=\delta e_1$, $x_4=\delta e_2$, where $0<\delta<1/(M-1) $. Moreover, assume that $c_1=c_2=0.5+\epsilon$, while $c_3=c_4=\epsilon$, for some small $\epsilon>0$. Suppose, for the sake of contradiction, that there exists a mechanism with approximation ratio $M$. Then, it must include in the solution $S$ at least one of $x_1$ or $x_2$: if not, then $V(S)\leq \delta^2$, while $OPT = (1+\delta)\delta$, a contradiction. Suppose thus that the solution contains $x_1$. By the monotonicity property, if the cost of experiment $x_1$ reduces to $B/2-3\epsilon$, $x_1$ will still be in the solution. By threshold payments, experiment $x_1$ receives in this case a payment that is at least $B/2+\epsilon$. By individual rationality and budget feasibility, $x_2$ cannot be included in the solution, so $V(S)$ is at most $(1+\delta)\delta$. However, the optimal solution includes all experiments, and yields $OPT=(1+\delta)^2$, a contradiction. %so the ratio is at least $(1+\delta)/\delta>M$. %\qed
+From Myerson's Theorem \cite{myerson}, a single parameter auction is truthful if and only if the allocation function is monotone and agents are paid theshold payments. Given $M>1$, consider $n=4$ experiments of dimension $d=2$. For $e_1,e_2$ the standard basis vectors in $\reals^2$, let $x_1 = e_1$, $x_2 = e_1$, and $x_3=\delta e_1$, $x_4=\delta e_2$, where $0<\delta<1/(M-1) $. Moreover, assume that $c_1=c_2=0.5+\epsilon$, while $c_3=c_4=\epsilon$, for some small $\epsilon>0$. Suppose, for the sake of contradiction, that there exists a mechanism with approximation ratio $M$. Then, it must include in the solution $S$ at least one of $x_1$ or $x_2$: if not, then $V(S)\leq \delta^2$, while $OPT = (1+\delta)\delta$, a contradiction. Suppose thus that the solution contains $x_1$. By the monotonicity property, if the cost of experiment $x_1$ reduces to $B/2-3\epsilon$, $x_1$ will still be in the solution. By threshold payments, experiment $x_1$ receives in this case a payment that is at least $B/2+\epsilon$. By individual rationality and budget feasibility, $x_2$ cannot be included in the solution, so $V(S)$ is at most $(1+\delta)\delta$. However, the optimal solution includes all experiments, and yields $OPT=(1+\delta)^2$, a contradiction. %so the ratio is at least $(1+\delta)/\delta>M$. %\qed