Fast nonlinear dimensionality reduction with topology preserving networks
Jakob J. Verbeek, Nikos Vlassis, Ben Kröse · Open Repository and Bibliography (University of Luxembourg) · 2002
Abstract. We present a fast alternative for the Isomap algorithm. A set of quantizers is ¯t to the data and a neighborhood structure based on the competitive Hebbian rule is imposed on it. This structure is used to obtain low-dimensional description of the data by means of comput-ing geodesic distances and multi dimensional scaling. The quantization allows for faster processing of the data. The speed-up as compared to Isomap is roughly quadratic in the ratio between the number of quan-tizers and the number of data points. The quantizers and neighborhood structure are use to map the data to the low dimensional space. 1