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» A new clustering algorithm for coordinate-free data
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UAI
2008
13 years 9 months ago
Flexible Priors for Exemplar-based Clustering
Exemplar-based clustering methods have been shown to produce state-of-the-art results on a number of synthetic and real-world clustering problems. They are appealing because they ...
Daniel Tarlow, Richard S. Zemel, Brendan J. Frey
CORR
2007
Springer
132views Education» more  CORR 2007»
13 years 8 months ago
Fast Algorithm and Implementation of Dissimilarity Self-Organizing Maps
In many real-world applications, data cannot be accurately represented by vectors. In those situations, one possible solution is to rely on dissimilarity measures that enable a se...
Brieuc Conan-Guez, Fabrice Rossi, Aïcha El Go...
ISNN
2011
Springer
12 years 11 months ago
Orthogonal Feature Learning for Time Series Clustering
This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
Xiaozhe Wang, Leo Lopes
NIPS
2004
13 years 9 months ago
Self-Tuning Spectral Clustering
We study a number of open issues in spectral clustering: (i) Selecting the appropriate scale of analysis, (ii) Handling multi-scale data, (iii) Clustering with irregular backgroun...
Lihi Zelnik-Manor, Pietro Perona
BMCBI
2005
112views more  BMCBI 2005»
13 years 8 months ago
Visualization methods for statistical analysis of microarray clusters
Background: The most common method of identifying groups of functionally related genes in microarray data is to apply a clustering algorithm. However, it is impossible to determin...
Matthew A. Hibbs, Nathaniel C. Dirksen, Kai Li, Ol...