XU Haixia and TIAN Zheng, “An Optimal Spectral Clustering Approach Based on Cauchy-Schwarz Divergence,” Chinese Journal of Electronics, vol. 18, no. 1, pp. 105-108, 2009,
Citation:
XU Haixia and TIAN Zheng, “An Optimal Spectral Clustering Approach Based on Cauchy-Schwarz Divergence,” Chinese Journal of Electronics, vol. 18, no. 1, pp. 105-108, 2009,
XU Haixia and TIAN Zheng, “An Optimal Spectral Clustering Approach Based on Cauchy-Schwarz Divergence,” Chinese Journal of Electronics, vol. 18, no. 1, pp. 105-108, 2009,
Citation:
XU Haixia and TIAN Zheng, “An Optimal Spectral Clustering Approach Based on Cauchy-Schwarz Divergence,” Chinese Journal of Electronics, vol. 18, no. 1, pp. 105-108, 2009,
A new global criterion, the CauchySchwarz (CS) cut, for spectral clustering is presented basedon the Cauchy-Schwarz divergence. It is proved thatwhen the sum of intra-cluster and inter-cluster similarity is fixed, optimizing the CS cut criterion can ensureintra-cluster similarity maximized and inter-cluster similarity minimized simultaneously. An effcient computational technique is developed based on eigenvalue problem.Experimental results on artificial data sets and natural images show that the proposed approach is very encouraging.