common features in all learning objects only. The In this paper, we propose two methods of clustering learning images to generate prototypes automatically for object recognition. O...
It presents some definitions of projected cluster and projected cluster group on hybrid attributes after having given some definitions on ordered attributes and sorted attributes t...
Given a data set, a dynamical procedure is applied to the data points in order to shrink and separate, possibly overlapping clusters. Namely, Newton’s equations of motion are em...
Abstract--Most well-known discriminative clustering models, such as spectral clustering (SC) and maximum margin clustering (MMC), are non-Bayesian. Moreover, they merely considered...
Spectral clustering algorithms have been shown to be more effective in finding clusters than some traditional algorithms such as k-means. However, spectral clustering suffers fro...