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ICPR
2008
IEEE
16 years 28 days ago
Categorization using semi-supervised clustering
Many applications require matching objects to a predefined, yet highly dynamic set of categories accompanied by category descriptions. We present a novel approach to solving this...
Jianying Hu, Moninder Singh, Aleksandra Mojsilovic
ACIVS
2006
Springer
16 years 14 days ago
Alternative Fuzzy Clustering Algorithms with L1-Norm and Covariance Matrix
In fuzzy clustering, the fuzzy c-means (FCM) algorithm is the best known and most used method. Although FCM is a very useful method, it is sensitive to noise and outliers so that W...
Miin-Shen Yang, Wen-Liang Hung, Tsiung-Iou Chung
ISPDC
2005
IEEE
16 years 2 days ago
On the Implementation and Evaluation of Berkeley Sockets on Maestro2 cluster computing environment
The support on cluster environments of ”legacy protocols” is important to avoid rewriting the code of applications, but this support should not prevent to achieve the maximum ...
Ricardo Guapo, Leonel Sousa, Shinichi Yamagiwa
ISPASS
2003
IEEE
15 years 11 months ago
On evaluating request-distribution schemes for saving energy in server clusters
Power-performance optimization is a relatively new problem area particularly in the context of server clusters. Poweraware request distribution is a method of scheduling service r...
Karthick Rajamani, Charles Lefurgy
ICDM
2002
IEEE
158views Data Mining» more  ICDM 2002»
15 years 11 months ago
Adaptive dimension reduction for clustering high dimensional data
It is well-known that for high dimensional data clustering, standard algorithms such as EM and the K-means are often trapped in local minimum. Many initialization methods were pro...
Chris H. Q. Ding, Xiaofeng He, Hongyuan Zha, Horst...