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ACIVS
2006
Springer
14 years 1 months 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
EUROPAR
2008
Springer
13 years 9 months ago
Mapping Heterogeneous Distributed Applications on Clusters
Performance of distributed applications largely depends on the mapping of their components on the underlying architecture. On one mponent-based approaches provide an abstraction su...
Sylvain Jubertie, Emmanuel Melin, Jér&eacut...
CLUSTER
2009
IEEE
13 years 5 months ago
Coordinating the use of GPU and CPU for improving performance of compute intensive applications
GPUs have recently evolved into very fast parallel co-processors capable of executing general purpose computations extremely efficiently. At the same time, multi-core CPUs evolutio...
George Teodoro, Rafael Sachetto Oliveira, Olcay Se...
BIBE
2007
IEEE
167views Bioinformatics» more  BIBE 2007»
13 years 12 months ago
Assessing the Performance of Macromolecular Sequence Classifiers
Machine learning approaches offer some of the most cost-effective approaches to building predictive models (e.g., classifiers) in a broad range of applications in computational bio...
Cornelia Caragea, Jivko Sinapov, Vasant Honavar, D...
ICDM
2009
IEEE
167views Data Mining» more  ICDM 2009»
13 years 5 months ago
Self-Adaptive Anytime Stream Clustering
Clustering streaming data requires algorithms which are capable of updating clustering results for the incoming data. As data is constantly arriving, time for processing is limited...
Philipp Kranen, Ira Assent, Corinna Baldauf, Thoma...