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134
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ICPR
2002
IEEE
16 years 4 months ago
Fast Hierarchical Clustering Based on Compressed Data
: One way to scale up clustering algorithms is to squash the data by some intelligent compression technique and cluster only the compressed data records. Such compressed data recor...
Erendira Rendon, Ricardo Barandela
KDD
2008
ACM
119views Data Mining» more  KDD 2008»
16 years 3 months ago
SAIL: summation-based incremental learning for information-theoretic clustering
Information-theoretic clustering aims to exploit information theoretic measures as the clustering criteria. A common practice on this topic is so-called INFO-K-means, which perfor...
Junjie Wu, Hui Xiong, Jian Chen
116
Voted
PDCAT
2005
Springer
15 years 9 months ago
Performance Study of Nonrigid Registration Algorithm for Investigating Lung Disease on Clusters
This paper presents a performance study of a nonrigid registration algorithm for investigating lung disease on clusters. Our algorithm combines two conventional acceleration techn...
Fumihiko Ino, Yuya Tanaka, Kenichi Hagihara, Hirok...
126
Voted
KDD
2004
ACM
190views Data Mining» more  KDD 2004»
16 years 3 months ago
Kernel k-means: spectral clustering and normalized cuts
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have re...
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
153
Voted
EWSN
2004
Springer
16 years 3 months ago
Improving the Energy Efficiency of Directed Diffusion Using Passive Clustering
Directed diffusion is a prominent example of data-centric routing based on application layer data and purely local interactions. In its functioning it relies heavily on network-wid...
Andreas Köpke, Christian Frank, Holger Karl, ...