We present an algorithm, Hierarchical ISOmetric SelfOrganizing Map (H-ISOSOM), for a concise, organized manifold representation of complex, non-linear, large scale, high-dimension...
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 ...
Inference of latent variables from complicated data is one important problem in data mining. The high dimensionality and high complexity of real world data often make accurate infe...
The neural representation of space in rats has inspired many navigation systems for robots. In particular, Self-Organizing (Feature) Maps (SOM) are often used to give a sense of lo...
Abstract. Recently, a new method intended to realize conformal mappings has been published. Called Locally Linear Embedding (LLE), this method can map high-dimensional data lying o...