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» Clustering for metric and non-metric distance measures
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RECOMB
2009
Springer
14 years 8 months ago
Finding Biologically Accurate Clusterings in Hierarchical Tree Decompositions Using the Variation of Information
Abstract. Hierarchical clustering is a popular method for grouping together similar elements based on a distance measure between them. In many cases, annotation information for som...
Saket Navlakha, James Robert White, Niranjan Nagar...
CVPR
2007
IEEE
14 years 9 months ago
Fiber Tract Clustering on Manifolds With Dual Rooted-Graphs
We propose a manifold learning approach to fiber tract clustering using a novel similarity measure between fiber tracts constructed from dual-rooted graphs. In particular, to gene...
Andy Tsai, Carl-Fredrik Westin, Alfred O. Hero, Al...
CIVR
2007
Springer
192views Image Analysis» more  CIVR 2007»
14 years 1 months ago
Texture retrieval based on a non-parametric measure for multivariate distributions
In the present study, an efficient strategy for retrieving texture images from large texture databases is introduced and studied within a distributional-statistical framework. Our...
Vasileios K. Pothos, Christos Theoharatos, George ...
TPDS
2002
173views more  TPDS 2002»
13 years 7 months ago
Data Gathering Algorithms in Sensor Networks Using Energy Metrics
Sensor webs consisting of nodes with limited battery power and wireless communications are deployed to collect useful information from the field. Gathering sensed information in an...
Stephanie Lindsey, Cauligi S. Raghavendra, Krishna...
ICALP
2009
Springer
14 years 7 months ago
Correlation Clustering Revisited: The "True" Cost of Error Minimization Problems
Correlation Clustering was defined by Bansal, Blum, and Chawla as the problem of clustering a set of elements based on a possibly inconsistent binary similarity function between e...
Nir Ailon, Edo Liberty