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KDD
2007
ACM
276views Data Mining» more  KDD 2007»
15 years 10 months ago
Nonlinear adaptive distance metric learning for clustering
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
Jianhui Chen, Zheng Zhao, Jieping Ye, Huan Liu
IJCAI
2007
14 years 11 months ago
A Scalable Kernel-Based Algorithm for Semi-Supervised Metric Learning
In recent years, metric learning in the semisupervised setting has aroused a lot of research interests. One type of semi-supervised metric learning utilizes supervisory informatio...
Dit-Yan Yeung, Hong Chang, Guang Dai
SIROCCO
2008
14 years 11 months ago
Distributed Approximation Algorithm for Resource Clustering
In this paper, we consider the clustering of resources on large scale platforms. More precisely, we target parallel applications consisting of independant tasks, where each task is...
Olivier Beaumont, Nicolas Bonichon, Philippe Ducho...
PKDD
2010
Springer
178views Data Mining» more  PKDD 2010»
14 years 8 months ago
Large-Scale Support Vector Learning with Structural Kernels
Abstract. In this paper, we present an extensive study of the cuttingplane algorithm (CPA) applied to structural kernels for advanced text classification on large datasets. In par...
Aliaksei Severyn, Alessandro Moschitti
CCGRID
2003
IEEE
15 years 3 months ago
MAGNET: A Tool for Debugging, Analyzing and Adapting Computing Systems
As computing systems grow in complexity, the cluster and grid communities require more sophisticated tools to diagnose, debug and analyze such systems. We have developed a toolkit...
Mark K. Gardner, Wu-chun Feng, Michael Broxton, Ad...