This paper proposes two methods which take advantage of k -mean clustering algorithm to decrease the number of support vectors (SVs) for the training of support vector machine (SVM...
Xiao-Lei Xia, Michael R. Lyu, Tat-Ming Lok, Guang-...
The segmentation of time-series is a constrained clustering problem: the data points should be grouped by their similarity, but with the constraint that all points in a cluster mus...
We propose a spectral learning approach to shape segmentation. The method is composed of a constrained spectral clustering algorithm that is used to supervise the segmentation of a...
The identification of categories in image databases usually relies on clustering algorithms that only exploit the feature-based similarities between images. The addition of semant...
Background: MapReduce is a parallel framework that has been used effectively to design largescale parallel applications for large computing clusters. In this paper, we evaluate th...