This paper demonstrates the applicability of the recently proposed supervised dimension reduction, hierarchical linear discriminant analysis (h-LDA) to a well-known spatial locali...
Clustering with partial supervision finds its application in situations where data is neither entirely nor accurately labeled. This paper discusses a semisupervised clustering algo...
We propose an Isometric Self-Organizing Map (ISOSOM) method for nonlinear dimensionality reduction, which integrates a Self-Organizing Map model and an ISOMAP dimension reduction ...
In this paper, we present a novel three-stage process to visualize the structure of point clouds in arbitrary dimensions. To get insight into the structure and complexity of a dat...
Representing images with layers has many important applications, such as video compression, motion analysis, and 3D scene analysis. This paper presents an approach to reliably ext...