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KDD
2007
ACM
159views Data Mining» more  KDD 2007»
16 years 8 days 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
15 years 5 months 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 3 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 1 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 1 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...