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ICML
2005
IEEE
14 years 8 months ago
Semi-supervised graph clustering: a kernel approach
Semi-supervised clustering algorithms aim to improve clustering results using limited supervision. The supervision is generally given as pairwise constraints; such constraints are...
Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Ray...
JSAC
2007
147views more  JSAC 2007»
13 years 7 months ago
Capacity limits of cognitive radio with distributed and dynamic spectral activity
Abstract— We investigate the capacity of opportunistic communication in the presence of dynamic and distributed spectral activity, i.e. when the time varying spectral holes sense...
Syed Ali Jafar, Sudhir Srinivasa
ECCV
2010
Springer
13 years 9 months ago
Learning Shape Segmentation Using Constrained Spectral Clustering and Probabilistic Label Transfer
We propose a spectral learning approach to shape segmentation. The method is composed of a constrained spectral clustering algorithm that is used to supervise the segmentation of a...
BMVC
2002
13 years 9 months ago
Alignment using Spectral Clusters
This paper describes a hierarchical spectral method for the correspondence matching of point-sets. Conventional spectral methods for correspondence matching are notoriously suscep...
Marco Carcassoni, Edwin R. Hancock
CVPR
2008
IEEE
14 years 9 months ago
Correlational spectral clustering
We present a new method for spectral clustering with paired data based on kernel canonical correlation analysis, called correlational spectral clustering. Paired data are common i...
Matthew B. Blaschko, Christoph H. Lampert