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Building k Edge-Disjoint Spanning Trees of Minimum Total Length for Isometric Data Embedding
October 2005 (vol. 27 no. 10)
pp. 1680-1683
ASCII Text
x 
 
Li Yang, "Building k Edge-Disjoint Spanning Trees of Minimum Total Length for Isometric Data Embedding," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, no. 10, pp. 1680-1683, October, 2005.
 
 
BibTex
x
 
@article{ 10.1109/TPAMI.2005.192,
author = {Li Yang},
title = {Building k Edge-Disjoint Spanning Trees of Minimum Total Length for Isometric Data Embedding},
journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume = {27},
number = {10},
issn = {0162-8828},
year = {2005},
pages = {1680-1683},
doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2005.192},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Pattern Analysis and Machine Intelligence
TI - Building k Edge-Disjoint Spanning Trees of Minimum Total Length for Isometric Data Embedding
IS - 10
SN - 0162-8828
SP1680
EP1683
EPD - 1680-1683
A1 - Li Yang,
PY - 2005
KW - Index Terms- Data embedding
KW - dimensionality reduction
KW - manifold learning
KW - minimum spanning tree
KW - neighborhood graph.
VL - 27
JA - IEEE Transactions on Pattern Analysis and Machine Intelligence
ER -
 
Li Yang, IEEE
Isometric data embedding requires construction of a neighborhood graph that spans all data points so that geodesic distance between any pair of data points could be estimated by distance along the shortest path between the pair on the graph. This paper presents an approach for constructing k-edge-connected neighborhood graphs. It works by finding k edge-disjoint spanning trees the sum of whose total lengths is a minimum. Experiments show that it outperforms the nearest neighbor approach for geodesic distance estimation.

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Index Terms:
Index Terms- Data embedding, dimensionality reduction, manifold learning, minimum spanning tree, neighborhood graph.
Citation:
Li Yang, "Building k Edge-Disjoint Spanning Trees of Minimum Total Length for Isometric Data Embedding," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, no. 10, pp. 1680-1683, Oct. 2005, doi:10.1109/TPAMI.2005.192
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