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» Limits of Spectral Clustering
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DIS
2006
Springer
14 years 4 days ago
Clustering Pairwise Distances with Missing Data: Maximum Cuts Versus Normalized Cuts
Abstract. Clustering algorithms based on a matrix of pairwise similarities (kernel matrix) for the data are widely known and used, a particularly popular class being spectral clust...
Jan Poland, Thomas Zeugmann
MVA
1996
223views Computer Vision» more  MVA 1996»
13 years 9 months ago
Classification of Rotated and Scaled Textured Images Using Spectral Moments
This paper describes a classification method for rotated and scaled textured images using invariant parameters based on spectral-moments. Although it is well known that rotation i...
Yasuo Yoshida, Yue Wu
AUTOMATICA
2000
72views more  AUTOMATICA 2000»
13 years 8 months ago
Direct iterative tuning via spectral analysis
This paper introduces a nonparametric frequency-domain scheme for tuning closed-loop systems. A linear quadratic criterion is used for guiding the system towards an optimal-regula...
Leonardo C. Kammer, Robert R. Bitmead, Peter L. Ba...
JAT
2010
39views more  JAT 2010»
13 years 7 months ago
On spectral polynomials of the Heun equation. I
The classical Heun equation has the form  Q(z) d2 dz2 + P (z) d dz + V (z) ff S(z) = 0, where Q(z) is a cubic complex polynomial, P (z) is a polynomial of degree at most 2 and ...
Boris Shapiro, Milos Tater
SDM
2009
SIAM
225views Data Mining» more  SDM 2009»
14 years 5 months ago
Integrated KL (K-means - Laplacian) Clustering: A New Clustering Approach by Combining Attribute Data and Pairwise Relations.
Most datasets in real applications come in from multiple sources. As a result, we often have attributes information about data objects and various pairwise relations (similarity) ...
Fei Wang, Chris H. Q. Ding, Tao Li