Fitting a graph to vector data
Author(s)
Daitch, Samuel I.; Kelner, Jonathan Adam
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We introduce a measure of how well a combinatorial
graph ts a collection of vectors.
The optimal graphs under this measure may
be computed by solving convex quadratic
programs and have many interesting properties.
For vectors in d dimensional space, the
graphs always have average degree at most
2(d+1), and for vectors in 2 dimensions they
are always planar. We compute these graphs
for many standard data sets and show that
they can be used to obtain good solutions to
classifi cation, regression and clustering problems.
Date issued
2009-01Department
Massachusetts Institute of Technology. Department of MathematicsJournal
Proceedings of the 26th Annual International Conference on Machine Learning
Publisher
Association for Computing Machinery
Citation
Samuel I. Daitch, Jonathan A. Kelner, and Daniel A. Spielman. 2009. Fitting a graph to vector data. In Proceedings of the 26th Annual International Conference on Machine Learning (ICML '09). ACM, New York, NY, USA, 201-208. DOI=10.1145/1553374.1553400 http://doi.acm.org/10.1145/1553374.1553400
Version: Author's final manuscript
ISBN
978-1-60558-516-1