Algorithms for nonlinear dimensionality reduction (NLDR) find meaningful hidden low-dimensional structures in a high-dimensional space. Current algorithms for NLDR are Isomaps, Local Linear Embedding and Laplacian Eigenmaps. Isomaps are able to reliably recover lowdimensional nonlinear structures in high-dimensional data sets, but suffer from the problem of short-circuiting, which occurs when t...