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PAKDD
2005
ACM
142views Data Mining» more  PAKDD 2005»
14 years 25 days ago
Dynamic Cluster Formation Using Level Set Methods
Density-based clustering has the advantages for (i) allowing arbitrary shape of cluster and (ii) not requiring the number of clusters as input. However, when clusters touch each o...
Andy M. Yip, Chris H. Q. Ding, Tony F. Chan
AINA
2008
IEEE
13 years 9 months ago
A Communication-Efficient Distributed Clustering Algorithm for Sensor Networks
Sensor networks usually generate continuous stream of data over time. Clustering sensor data as a core task of mining sensor data plays an essential role in analytical application...
Amirhosein Taherkordi, Reza Mohammadi, Frank Elias...
HPCN
1999
Springer
13 years 11 months ago
JAVA as a Basis for Parallel Data Mining in Workstation Clusters
Matthias Gimbel, Michael Philippsen, Bernhard Haum...
IDA
2003
Springer
14 years 17 days ago
Fuzzy Clustering of Short Time-Series and Unevenly Distributed Sampling Points
This paper proposes a new clustering algorithm in the fuzzy-c-means family, which is designed to cluster time series and is particularly suited for short time series and those wit...
Carla S. Möller-Levet, Frank Klawonn, Kwang-H...
ICASSP
2010
IEEE
13 years 7 months ago
Learning from high-dimensional noisy data via projections onto multi-dimensional ellipsoids
In this paper, we examine the problem of learning from noisecontaminated data in high-dimensional space. A new learning approach based on projections onto multi-dimensional ellips...
Liuling Gong, Dan Schonfeld