Spectral clustering by recursive partitioning (2006)
| Venue: | In ESA |
| Citations: | 7 - 0 self |
BibTeX
@INPROCEEDINGS{Dasgupta06spectralclustering,
author = {Anirban Dasgupta and John Hopcroft and Ravi Kannan and Pradipta Mitra},
title = {Spectral clustering by recursive partitioning},
booktitle = {In ESA},
year = {2006},
pages = {256--267}
}
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Abstract
In this paper, we analyze the second eigenvector technique of spectral partitioning on the planted partition random graph model, by constructing a recursive algorithm using the second eigenvectors in order to learn the planted partitions. The correctness of our algorithm is not based on the ratio-cut interpretation of the second eigenvector, but exploits instead the stability of the eigenvector subspace. As a result, we get an improved cluster separation bound in terms of dependence on the maximum variance. We also extend our results for a clustering problem in the case of sparse graphs. 1
