[mlpack-git] master, mlpack-1.0.x: Update citation format. (a07b4eb)

[gitdub at big.cc.gt.atl.ga.us]

Repository : https://github.com/mlpack/mlpack

On branches: master,mlpack-1.0.x
Link       : https://github.com/mlpack/mlpack/compare/904762495c039e345beba14c1142fd719b3bd50e...f94823c800ad6f7266995c700b1b630d5ffdcf40

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commit a07b4eb6090bb30f08a762992b846b97d8db2c25
Author: Ryan Curtin <ryan at ratml.org>
Date:   Tue Feb 11 16:46:48 2014 +0000

    Update citation format.


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a07b4eb6090bb30f08a762992b846b97d8db2c25
 doc/tutorials/emst/emst.txt | 18 ++++++++++++++++--
 1 file changed, 16 insertions(+), 2 deletions(-)

diff --git a/doc/tutorials/emst/emst.txt b/doc/tutorials/emst/emst.txt
index f03100a..44ecea6 100644
--- a/doc/tutorials/emst/emst.txt
+++ b/doc/tutorials/emst/emst.txt
@@ -17,8 +17,22 @@ Among other applications, the EMST can be used to compute hierarchical clusterin
 of data.  A <em>single-linkage clustering</em> can be obtained from the EMST by deleting
 all edges longer than a given cluster length.  This technique is also referred to as a <em>Friends-of-Friends</em> clustering in the astronomy literature.
 
-MLPACK includes an implementation of <b>Dual-Tree Boruvka</b> on \f$kd\f$-trees, the empirically and
-theoretically fastest EMST algorithm.  For more details, see March, <em>et al.</em>, <em>Euclidean Minimum Spanning Tree: Algorithm, Analysis, and Applications</em>, in KDD, 2010.  An implementation using cover trees is forthcoming.
+MLPACK includes an implementation of <b>Dual-Tree Boruvka</b> on \f$kd\f$-trees,
+the empirically and theoretically fastest EMST algorithm.  For more details,
+see the following paper:
+
+ at code
+ at inproceedings{march2010fast,
+  title={Fast {E}uclidean minimum spanning tree: algorithm, analysis, and
+applications},
+  author={March, William B. and Ram, Parikshit and Gray, Alexander G.},
+  booktitle={Proceedings of the 16th ACM SIGKDD International Conference on
+Knowledge Discovery and Data Mining (KDD '10)},
+  pages={603--612},
+  year={2010},
+  organization={ACM}
+}
+ at endcode
 
 \b mlpack provides: