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SDM
2009
SIAM
144views Data Mining» more  SDM 2009»
14 years 8 months ago
CORE: Nonparametric Clustering of Large Numeric Databases.
Current clustering techniques are able to identify arbitrarily shaped clusters in the presence of noise, but depend on carefully chosen model parameters. The choice of model param...
Andrej Taliun, Arturas Mazeika, Michael H. Bö...
CIKM
2009
Springer
14 years 5 months ago
Fragment-based clustering ensembles
Clustering ensembles combine different clustering solutions into a single robust and stable one. Most of existing methods become highly time-consuming when the data size turns to ...
Ou Wu, Mingliang Zhu, Weiming Hu
ICPR
2008
IEEE
14 years 5 months ago
Adaptive selection of non-target cluster centers for K-means tracker
Hua et al. have proposed a stable and efficient tracking algorithm called “K-means tracker”[2, 3, 5]. This paper describes an adaptive non-target cluster center selection met...
Hiroshi Oike, Haiyuan Wu, Toshikazu Wada
MICCAI
1999
Springer
14 years 3 months ago
Statistical Segmentation of fMRI Activations Using Contextual Clustering
Abstract. A central problem in the analysis of functional magnetic resonance imaging (fMRI) data is the reliable detection and segmentation of activated areas. Often this goal is a...
Eero Salli, Ari Visa, Hannu J. Aronen, Antti Korve...
PRIS
2004
14 years 4 days ago
Comparison of Combination Methods using Spectral Clustering Ensembles
We address the problem of the combination of multiple data partitions, that we call a clustering ensemble. We use a recent clustering approach, known as Spectral Clustering, and th...
André Lourenço, Ana L. N. Fred