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KDD
2007
ACM
159views Data Mining» more  KDD 2007»
16 years 7 months ago
Constraint-driven clustering
Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...
Rong Ge, Martin Ester, Wen Jin, Ian Davidson
DIAGRAMS
2004
Springer
16 years 7 days ago
Geographic Projection of Cluster Composites
A composite cluster map displays a fuzzy categorisation of geographic areas. It combines information from several sources to provide a visualisation of the significance of cluster...
Peter Kleiweg, John Nerbonne, Leonie Bosveld
KDD
2010
ACM
245views Data Mining» more  KDD 2010»
15 years 10 months ago
Flexible constrained spectral clustering
Constrained clustering has been well-studied for algorithms like K-means and hierarchical agglomerative clustering. However, how to encode constraints into spectral clustering rem...
Xiang Wang, Ian Davidson
CVPR
2004
IEEE
16 years 8 months ago
Robust Subspace Clustering by Combined Use of kNND Metric and SVD Algorithm
Subspace clustering has many applications in computer vision, such as image/video segmentation and pattern classification. The major issue in subspace clustering is to obtain the ...
Qifa Ke, Takeo Kanade
ECCV
2002
Springer
16 years 8 months ago
Nonlinear Shape Statistics in Mumford-Shah Based Segmentation
We present a variational integration of nonlinear shape statistics into a Mumford?Shah based segmentation process. The nonlinear statistics are derived from a set of training silho...
Christoph Schnörr, Daniel Cremers, Timo Kohlb...