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ICCS
2005
Springer
15 years 3 months ago
Dimension Reduction for Clustering Time Series Using Global Characteristics
Existing methods for time series clustering rely on the actual data values can become impractical since the methods do not easily handle dataset with high dimensionality, missing v...
Xiaozhe Wang, Kate A. Smith, Rob J. Hyndman
ICDM
2003
IEEE
130views Data Mining» more  ICDM 2003»
15 years 3 months ago
Information Theoretic Clustering of Sparse Co-Occurrence Data
A novel approach to clustering co-occurrence data poses it as an optimization problem in information theory which minimizes the resulting loss in mutual information. A divisive cl...
Inderjit S. Dhillon, Yuqiang Guan
ICPR
2006
IEEE
15 years 11 months ago
Robust Tracking of Multiple People in Crowds Using Laser Range Scanners
Laser based people tracking systems have been developed for mobile robotic or intelligent surveillance areas. Existing systems rely on laser point clustering to extract object loc...
Jinshi Cui, Hongbin Zha, Huijing Zhao, Ryosuke Shi...
ICML
2009
IEEE
15 years 10 months ago
Multi-assignment clustering for Boolean data
Conventional clustering methods typically assume that each data item belongs to a single cluster. This assumption does not hold in general. In order to overcome this limitation, w...
Andreas P. Streich, Mario Frank, David A. Basin, J...
SDM
2009
SIAM
144views Data Mining» more  SDM 2009»
15 years 7 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...