Many unsupervised algorithms for nonlinear dimensionality reduction, such as locally linear embedding (LLE) and Laplacian eigenmaps, are derived from the spectral decompositions o...
Fundamental to the generation of 3D audio is the HRTF processing of acoustical signals. Unfortunately, given the high dimensionality of HRTFs, incorporating them into dynamic/inte...
Dimensionality reduction involves mapping a set of high dimensional input points onto a low dimensional manifold so that "similar" points in input space are mapped to ne...
Traditional visualization techniques for multidimensional data sets, such as parallel coordinates, glyphs, and scatterplot matrices, do not scale well to high numbers of dimension...
Jing Yang, Matthew O. Ward, Elke A. Rundensteiner,...
Linear Discriminant Analysis (LDA), which works by maximizing the within-class similarity and minimizing the between-class similarity simultaneously, is a popular dimensionality r...