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» Spectral Methods for Automatic Multiscale Data Clustering
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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
DAGSTUHL
2010
13 years 9 months ago
Saliency Guided Summarization of Molecular Dynamics Simulations
We present a novel method to measure saliency in molecular dynamics simulation data. This saliency measure is based on a multiscale center-surround mechanism, which is fast and ef...
Robert Patro, Cheuk Yiu Ip, Amitabh Varshney
ICML
2007
IEEE
14 years 8 months ago
Spectral clustering and transductive learning with multiple views
We consider spectral clustering and transductive inference for data with multiple views. A typical example is the web, which can be described by either the hyperlinks between web ...
Dengyong Zhou, Christopher J. C. Burges
MVA
2000
122views Computer Vision» more  MVA 2000»
13 years 9 months ago
Unsupervised Classification of X-Ray Mapping Images of Polished Sections
X-ray mapping images of polished sections are classified using two unsupervised clustering algorithms. The methods applied are the k-means algorithm and an extended spectral fuzzy...
Klaus Baggesen Hilger, Allan Aasbjerg Nielsen, Jen...
PAKDD
2004
ACM
96views Data Mining» more  PAKDD 2004»
14 years 1 months ago
Spectral Energy Minimization for Semi-supervised Learning
The use of unlabeled data to aid classification is important as labeled data is often available in limited quantity. Instead of utilizing training samples directly into semi-super...
Chun Hung Li, Zhi-Li Wu