Abstract. Constrained clustering investigates how to incorporate domain knowledge in the clustering process. The domain knowledge takes the form of constraints that must hold on th...
Face representation based on the Visual Codebook becomes popular because of its excellent recognition performance, in which the critical problem is how to learn the most efficien...
We investigate how random projection can best be used for clustering high dimensional data. Random projection has been shown to have promising theoretical properties. In practice,...
Abstract—The multi-band target detection algorithms implemented in hyperspectral imaging systems represent perhaps the most successful example of image fusion. A core suite of su...
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...