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» Graph-Theoretic Approach to Clustering and Segmentation
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PR
2007
189views more  PR 2007»
13 years 3 months ago
Information cut for clustering using a gradient descent approach
We introduce a new graph cut for clustering which we call the Information Cut. It is derived using Parzen windowing to estimate an information theoretic distance measure between p...
Robert Jenssen, Deniz Erdogmus, Kenneth E. Hild II...
CVPR
1999
IEEE
14 years 6 months ago
Stochastic Image Segmentation by Typical Cuts
We present a stochastic clustering algorithm which uses pairwise similarity of elements, based on a new graph theoretical algorithm for the sampling of cuts in graphs. The stochas...
Yoram Gdalyahu, Daphna Weinshall, Michael Werman
BMCBI
2011
12 years 11 months ago
Ultra-fast sequence clustering from similarity networks with SiLiX
Background: The number of gene sequences that are available for comparative genomics approaches is increasing extremely quickly. A current challenge is to be able to handle this h...
Vincent Miele, Simon Penel, Laurent Duret
WG
2010
Springer
13 years 2 months ago
Generalized Graph Clustering: Recognizing (p, q)-Cluster Graphs
Cluster Editing is a classical graph theoretic approach to tackle the problem of data set clustering: it consists of modifying a similarity graph into a disjoint union of cliques,...
Pinar Heggernes, Daniel Lokshtanov, Jesper Nederlo...
EMMCVPR
2001
Springer
13 years 8 months ago
Path Based Pairwise Data Clustering with Application to Texture Segmentation
Most cost function based clustering or partitioning methods measure the compactness of groups of data. In contrast to this picture of a point source in feature space, some data sou...
Bernd Fischer, Thomas Zöller, Joachim M. Buhm...