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authorThibaut Horel <thibaut.horel@gmail.com>2012-11-02 15:15:50 +0100
committerThibaut Horel <thibaut.horel@gmail.com>2012-11-02 15:15:50 +0100
commit4d665f8693faf85ee20556508db27b86bb62f219 (patch)
tree044660530ea99948a2dafe37238c3b7787b09cb0 /general.tex
parentb6aa0b124de02bda659db226ef66f1886f98252e (diff)
downloadrecommendation-4d665f8693faf85ee20556508db27b86bb62f219.tar.gz
Compute the constant in the upper bound of the general theorem
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@@ -57,19 +57,14 @@ For two reasons:
For the function $\tilde{V}$ defined above, there is a truthful, budget
feasible mechanism which achieves an approximation ratio of:
\begin{displaymath}
- \frac{5e-1}{e-1}\frac{\log(1+\mu)}{\mu} + A
+ \frac{5e-1}{e-1}\frac{2\mu}{\log(1+\mu)} + 5.1
\end{displaymath}
-where $\mu$ is the smallest eigenvalue of $R$ (and $A$ is a constant that
-I will compute tomorrow, it should be roughly around 10).
+where $\mu$ is the smallest eigenvalue of $R$.
\end{theorem}
Note that everything becomes nice when $R \geq I_d$. In this case, the smallest
eigenvalue is larger than 1. Hence $\log\det R\geq 0$ and an approximation on
$\tilde{V}$ gives an approximation ration on $V$ (see discussion above).
-Furthermore, we can bound $\log(1+\mu)/\mu$ by 1 and I think we fall back on
-the approximation ratio of section 2.
-
-Can we motivate that $R\geq 1$ ?
\subsection{Beyond Linear Models}
TODO: Independent noise model. Captures models such as logistic regression, classification, etc. Arbitrary prior. Show that change in the entropy is submodular (cite Krause, Guestrin).