A randomized algorithm for spectral clustering

Proceedings of the 18th European Symposium on Artificial Neural Networks - Computational Intelligence and Machine Learning, ESANN 2010

Volumn , Issue , 2010, Pages 381-386

  Rebagliati, Nicola ^a   Verri, Alessandro ^a  

^a UNIVERSITY OF GENOA   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERING SOLUTIONS; NORMALIZED LAPLACIAN; NUMBER OF CLASS; RANDOMIZED ALGORITHMS; REAL-WORLD GRAPHS; SPECTRAL ALGORITHM; SPECTRAL CLUSTERING;

EIGENVALUES AND EIGENFUNCTIONS; LEARNING SYSTEMS; NEURAL NETWORKS;

ALGORITHMS;

EID: 84887001092     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (17)

1. J. Shi and J. Malik. Normalized cuts and image segmentation. PAMI, 22, 1997.
2. S. Guattery and G. L. Miller. On the performance of spectral graph partitioning methods. In SODA, 1995.
3. N. Rebagliati and A. Verri. A randomized approach to spectral clustering. Technical Report DISI-TR-09-08, DISI, 2009.
4. M. Meilǎ and J. Shi. Learning segmentation by random walks. In NIPS, 2000.
5. A. Y. Ng, M. I. Jordan, and Y. Weiss. On spectral clustering: Analysis and an algorithm. In NIPS, 2001.
6. C. H. Q. Ding and X. He. K-means clustering via principal component analysis. In ICML, 2004.
7. F. R. Bach and M. I. Jordan. Learning spectral clustering, with application to speech separation. JMLR, 7, 2006.
8. M. Fiedler. A property of eigenvectors of nonnegative symmetric matrices and its application to graph theory. Czechoslovak Mathematical Journal, 25, 1975.
9. W.E. Donath and A.J. Hoffman. Lower bounds for the partitioning of graphs. IBM J.Res.Develop., 17, 1973.
10. C. J. Alpert and A. B. Kahng. Recent directions in netlist partitioning: A survey. Integration: The VLSI Journal, 19, 1995.
11. J. A. Frankle and R. M. Karp. Circuit placement by eigenvector decomposition. In ICCAD, 1986.
12. C. J. Alpert and S. Yao. Spectral partitioning: The more eigenvectors, the better. In DAC, 1995.
13. T. Xiang and S. Gong. Spectral clustering with eigenvector selection. Pattern Recogn., 41(3), 2008.
14. U. von Luxburg. A tutorial on spectral clustering. Statistics and Computing, 17, 2007.
15. M. Meilǎ. The uniqueness of a good optimum for k-means. In ICML, 2006.
16. P.-A. Absil, A. Edelman, and P. Koev. On the largest principal angle between random subspaces. Linear Algebra Appl., 414(1), 2006.
17. A. J. Soper, C. Walshaw, and M. Cross. A combined evolutionary search and multilevel approach to graph partitioning. London SE10 9LS, 29, 2000.