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EDBT
2004
ACM
142views Database» more  EDBT 2004»
15 years 10 months ago
Iterative Incremental Clustering of Time Series
We present a novel anytime version of partitional clustering algorithm, such as k-Means and EM, for time series. The algorithm works by leveraging off the multi-resolution property...
Jessica Lin, Michail Vlachos, Eamonn J. Keogh, Dim...
IPMI
2009
Springer
15 years 4 months ago
Clustering of the Human Skeletal Muscle Fibers Using Linear Programming and Angular Hilbertian Metrics
In this paper, we present a manifold clustering method for the classification of fibers obtained from diffusion tensor images (DTI) of the human skeletal muscle. Using a linear ...
Radhouène Neji, Ahmed Besbes, Nikos Komodak...
ISPAN
2005
IEEE
15 years 3 months ago
A Scalable Method for Predicting Network Performance in Heterogeneous Clusters
An important requirement for the effective scheduling of parallel applications on large heterogeneous clusters is a current view of system resource availability. Maintaining such ...
Dimitrios Katramatos, Steve J. Chapin
ESA
2009
Springer
167views Algorithms» more  ESA 2009»
15 years 2 months ago
Clustering-Based Bidding Languages for Sponsored Search
Sponsored search auctions provide a marketplace where advertisers can bid for millions of advertising opportunities to promote their products. The main difficulty facing the adver...
Mohammad Mahdian, Grant Wang
EMMCVPR
2001
Springer
15 years 2 months ago
Path Based Pairwise Data Clustering with Application to Texture Segmentation
Most cost function based clustering or partitioning methods measure the compactness of groups of data. In contrast to this picture of a point source in feature space, some data sou...
Bernd Fischer, Thomas Zöller, Joachim M. Buhm...