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...
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...
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...
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...
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...