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Gilson António Giraldi (National Laboratory for Scientific Computing), Carlos Eduardo Thomaz (University Center of FEI), Gastão Florencio Miranda (Universidade Federal de Sergipe)
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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).
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