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ICML
2006
IEEE
14 years 9 months ago
A continuation method for semi-supervised SVMs
Semi-Supervised Support Vector Machines (S3 VMs) are an appealing method for using unlabeled data in classification: their objective function favors decision boundaries which do n...
Olivier Chapelle, Mingmin Chi, Alexander Zien
CLUSTER
1999
IEEE
13 years 8 months ago
Simulative performance analysis of gossip failure detection for scalable distributed systems
Three protocols for gossip-based failure detection services in large-scale heterogeneous clusters are analyzed and compared. The basic gossip protocol provides a means by which fai...
Mark W. Burns, Alan D. George, Bradley A. Wallace
ICML
2010
IEEE
13 years 6 months ago
Mining Clustering Dimensions
Many real-world datasets can be clustered along multiple dimensions. For example, text documents can be clustered not only by topic, but also by the author's gender or sentim...
Sajib Dasgupta, Vincent Ng
CANPC
2000
Springer
14 years 26 days ago
Transparent Network Connectivity in Dynamic Cluster Environments
Improvements in microprocessor and networking performance have made networks of workstations a very attractive platform for high-end parallel and distributed computing. However, t...
Xiaodong Fu, Hua Wang, Vijay Karamcheti
ICPR
2006
IEEE
14 years 9 months ago
A Comparison of Texture Features Based on SVM and SOM
Experimental results of texture features derived from Gabor and other four wavelet transforms classified and clustered based on Support Vector Machine (SVMs) and Self-Organizing M...
Chaur-Chin Chen, Chien-Chang Chen, Chih-Ming Chen