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authorThibaut Horel <thibaut.horel@gmail.com>2012-10-01 18:15:51 -0700
committerThibaut Horel <thibaut.horel@gmail.com>2012-10-01 18:15:51 -0700
commit3cd73c735e26805d449ac73cefac5b5fa43e2590 (patch)
tree13ab8930f3a5ebc2ee6fd71e24d91d59291e23e6
parentf391c47d9265c19982afc9bef4869e1ca32789dd (diff)
downloadrecommendation-3cd73c735e26805d449ac73cefac5b5fa43e2590.tar.gz
Fix a typo, add a remark about the value function
-rw-r--r--notes.tex18
1 files changed, 14 insertions, 4 deletions
diff --git a/notes.tex b/notes.tex
index ec0435c..1ce4cc4 100644
--- a/notes.tex
+++ b/notes.tex
@@ -1,7 +1,7 @@
-\documentclass[twocolumn]{article}
+\documentclass{IEEEtran}
+%\usepackage{mathptmx}
\usepackage[utf8]{inputenc}
\usepackage{amsmath,amsthm,amsfonts}
-\usepackage{comment}
\newtheorem{lemma}{Lemma}
\newtheorem{fact}{Fact}
\newtheorem{example}{Example}
@@ -16,6 +16,7 @@
\DeclareMathOperator{\trace}{tr}
\DeclareMathOperator*{\argmax}{arg\,max}
\title{Value of data}
+\author{Stratis Ionnadis \and Thibaut Horel}
\begin{document}
\maketitle
@@ -160,12 +161,12 @@ The payment received by user $i$ will be denoted by $p_i$.
The mechanism should satisfy the following conditions:
\begin{itemize}
\item \textbf{Normalized} if $s_i = 0$ then $p_i = 0$.
- \item \textbf{Indiviually rational} $p_i \geq s_ic_i$.
+ \item \textbf{Individually rational} $p_i \geq s_ic_i$.
\item \textbf{Truthful} $p_i - s_ic_i \geq p_i' - s_i'c_i$, where $p_i'$
and $s_i'$ are the payment and allocation of user $i$ had he reported
a cost $c_i'$ different from his true cost $c_i$ (keeping the costs
reported by the other users the same).
- \item \textbf{Budget feasible} the payments should be withing budget:
+ \item \textbf{Budget feasible} the payments should be within budget:
\begin{displaymath}
\sum_{i\in \mathcal{I}} s_ip_i \leq B
\end{displaymath}
@@ -360,6 +361,15 @@ Finally, we can use the Sylvester's formula to get the result.
it is clear that our value function is non-decreasing and submodular.
The positivity follows from a direct application of the spectral
theorem.
+ \item the matrix which appears in the value function:
+ \begin{displaymath}
+ I_d + \frac{\Sigma}{\sigma^2}X_S^*X_S
+ \end{displaymath}
+ is also the inverse of the covariance matrix of the ridge regression
+ estimator. In optimal experiment design, it is common to use the
+ determinant of the inverse of the estiamator's covariance matrix as
+ a mesure of the quality of the predicion. Indeed, this directly relates to
+ the inverse of the volume of the confidence ellipsoid.
\item This value function can be computed up to a fixed decimal precision in
polynomial time.
\end{enumerate}