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| author | Thibaut Horel <thibaut.horel@gmail.com> | 2012-11-05 02:18:05 +0100 |
|---|---|---|
| committer | Thibaut Horel <thibaut.horel@gmail.com> | 2012-11-05 02:18:31 +0100 |
| commit | 2a4664283998d5bf9c6615d251fd62c30001b73e (patch) | |
| tree | 1554852eba4f43f1c6bc356d1df665ba6cd066f3 | |
| parent | 86b8f967a12fe5870fe7c8d0f765149c003832c6 (diff) | |
| download | recommendation-2a4664283998d5bf9c6615d251fd62c30001b73e.tar.gz | |
Fix missing references
| -rw-r--r-- | general.tex | 6 | ||||
| -rw-r--r-- | notes.bib | 32 |
2 files changed, 35 insertions, 3 deletions
diff --git a/general.tex b/general.tex index 4f9aaad..550d6b7 100644 --- a/general.tex +++ b/general.tex @@ -79,13 +79,13 @@ The value function given by the information gain \eqref{general} is submodular. \end{lemma} \begin{proof} -The theorem is proved in a slightly different context in \cite{guestrin}; we +The theorem is proved in a slightly different context in \cite{krause2005near}; we repeat the proof here for the sake of completeness. Using the chain rule for the conditional entropy we get: -\begin{displaymath}\label{eq:chain-rule} +\begin{equation}\label{eq:chain-rule} V(S) = H(y_S) - H(y_S \mid \beta) = H(y_S) - \sum_{i\in S} H(y_i \mid \beta) -\end{displaymath} +\end{equation} where the second equality comes from the independence of the $y_i$'s conditioned on $\beta$. Recall that the joint entropy of a set of random variables is a submodular function. Thus, our value function is written in @@ -498,3 +498,35 @@ bibsource = {DBLP, http://dblp.uni-trier.de} } +@inproceedings{krause2005near, + author = {Andreas Krause and + Carlos Guestrin}, + 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} +} + +@proceedings{DBLP:conf/uai/2005, + title = {UAI '05, Proceedings of the 21st Conference in Uncertainty + in Artificial Intelligence, Edinburgh, Scotland, July 26-29, + 2005}, + booktitle = {UAI}, + publisher = {AUAI Press}, + year = {2005}, + isbn = {0-9749039-1-4}, + bibsource = {DBLP, http://dblp.uni-trier.de} +} + +@book{hastie, + title={The elements of statistical learning}, + author={Friedman, J. and Hastie, T. and Tibshirani, R.}, + volume={1}, + year={2001}, + publisher={Springer Series in Statistics} +} + |
