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ECML
2006
Springer
13 years 9 months ago
B-Matching for Spectral Clustering
We propose preprocessing spectral clustering with b-matching to remove spurious edges in the adjacency graph prior to clustering. B-matching is a generalization of traditional maxi...
Tony Jebara, Vlad Shchogolev
CVPR
2006
IEEE
14 years 9 months ago
Graph Partitioning by Spectral Rounding: Applications in Image Segmentation and Clustering
ct We introduce a new family of spectral partitioning methods. Edge separators of a graph are produced by iteratively reweighting the edges until the graph disconnects into the pre...
David Tolliver, Gary L. Miller
PR
2008
169views more  PR 2008»
13 years 7 months ago
A survey of kernel and spectral methods for clustering
Clustering algorithms are a useful tool to explore data structures and have been employed in many disciplines. The focus of this paper is the partitioning clustering problem with ...
Maurizio Filippone, Francesco Camastra, Francesco ...
PAKDD
2011
ACM
209views Data Mining» more  PAKDD 2011»
12 years 10 months ago
Spectral Analysis for Billion-Scale Graphs: Discoveries and Implementation
Abstract. Given a graph with billions of nodes and edges, how can we find patterns and anomalies? Are there nodes that participate in too many or too few triangles? Are there clos...
U. Kang, Brendan Meeder, Christos Faloutsos
EUSFLAT
2009
152views Fuzzy Logic» more  EUSFLAT 2009»
13 years 5 months ago
Learning Fuzzy Rule Based Classifier in High Performance Computing Environment
-- An approach to estimate the number of rules by spectral analysis of the training dataset has been recently proposed [1]. This work presents an analysis of such a method in high ...
Vinicius da F. Vieira, Alexandre Evsukoff, Beatriz...