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ICAI
2004
13 years 9 months ago
A Comparison of Resampling Methods for Clustering Ensembles
-- Combination of multiple clusterings is an important task in the area of unsupervised learning. Inspired by the success of supervised bagging algorithms, we propose a resampling ...
Behrouz Minaei-Bidgoli, Alexander P. Topchy, Willi...
ECML
2006
Springer
13 years 10 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
KBS
2006
150views more  KBS 2006»
13 years 8 months ago
Clusterer ensemble
Ensemble methods that train multiple learners and then combine their predictions have been shown to be very effective in supervised learning. This paper explores ensemble methods ...
Zhi-Hua Zhou, Wei Tang
ICML
2005
IEEE
14 years 8 months ago
Analysis and extension of spectral methods for nonlinear dimensionality reduction
Many unsupervised algorithms for nonlinear dimensionality reduction, such as locally linear embedding (LLE) and Laplacian eigenmaps, are derived from the spectral decompositions o...
Fei Sha, Lawrence K. Saul
AINA
2007
IEEE
14 years 2 months ago
A Semi-Automatic Framework for Mining ERP Patterns
Event-related potentials (ERP) are brain electrophysiological patterns created by averaging electroencephalographic (EEG) data, time-locking to events of interest (e.g., stimulus ...
Jiawei Rong, Dejing Dou, Gwen A. Frishkoff, Robert...