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NIPS
2004
13 years 8 months ago
Limits of Spectral Clustering
An important aspect of clustering algorithms is whether the partitions constructed on finite samples converge to a useful clustering of the whole data space as the sample size inc...
Ulrike von Luxburg, Olivier Bousquet, Mikhail Belk...
ECCV
2010
Springer
13 years 10 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 10 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
DEXA
2010
Springer
156views Database» more  DEXA 2010»
13 years 8 months ago
Improving Alternative Text Clustering Quality in the Avoiding Bias Task with Spectral and Flat Partition Algorithms
Abstract. The problems of finding alternative clusterings and avoiding bias have gained popularity over the last years. In this paper we put the focus on the quality of these alter...
M. Eduardo Ares, Javier Parapar, Alvaro Barreiro