Linearized cluster assignment via spectral ordering

@inproceedings{Ding2004LinearizedCA,
  title={Linearized cluster assignment via spectral ordering},
  author={Chris H. Q. Ding and Xiaofeng He},
  booktitle={ICML},
  year={2004}
}
Spectral clustering uses eigenvectors of the Laplacian of the similarity matrix. They are most conveniently applied to 2-way clustering problems. When applying to multi-way clustering, either the 2-way spectral clustering is recursively applied or an embedding to spectral space is done and some other methods are used to cluster the points. Here we propose and study a K-way cluster assignment method. The method transforms the problem to find valleys and peaks of a 1-D quantity called cluster… CONTINUE READING
Highly Cited
This paper has 105 citations. REVIEW CITATIONS

Topics

Statistics

01020'05'07'09'11'13'15'17
Citations per Year

105 Citations

Semantic Scholar estimates that this publication has 105 citations based on the available data.

See our FAQ for additional information.