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» Spatially Coherent Clustering Using Graph Cuts
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AAIM
2008
Springer
119views Algorithms» more  AAIM 2008»
14 years 2 months ago
Engineering Comparators for Graph Clusterings
A promising approach to compare two graph clusterings is based on using measurements for calculating the distance between them. Existing measures either use the structure of cluste...
Daniel Delling, Marco Gaertler, Robert Görke,...
UAI
2003
13 years 9 months ago
Learning Generative Models of Similarity Matrices
Recently, spectral clustering (a.k.a. normalized graph cut) techniques have become popular for their potential ability at finding irregularlyshaped clusters in data. The input to...
Rómer Rosales, Brendan J. Frey
VISSYM
2007
13 years 10 months ago
Functional Unit Maps for Data-Driven Visualization of High-Density EEG Coherence
Synchronous electrical activity in different brain regions is generally assumed to imply functional relationships between these regions. A measure for this synchrony is electroenc...
Michael ten Caat, Natasha M. Maurits, Jos B. T. M....
ECCV
2004
Springer
14 years 1 months ago
Probabilistic Spatial-Temporal Segmentation of Multiple Sclerosis Lesions
Abstract. In this paper we describe the application of a novel statistical videomodeling scheme to sequences of multiple sclerosis (MS) images taken over time. The analysis of the ...
Allon Shahar, Hayit Greenspan
SDM
2009
SIAM
225views Data Mining» more  SDM 2009»
14 years 4 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