Back
Gastão Florencio Miranda (Universidade Federal de Sergipe), Gilson António Giraldi (National Laboratory for Scientific Computing), Carlos Eduardo Thomaz (University Center of FEI)
Author/s
About the resource/s
The conference paper gives in the first section a brief and easy understandable introduction into the basics of Riemannian geometry. Furthermore, it gives a review of classical methods for mapping data into a low-dimensional manifold / nonlinear dimensionality reduction like Local Linear Embedding (LLE), Isometric Feature Mapping (ISOMAP) and Local Riemannian Manifold Learning (LRML).
Other Sources
