Random Projections for Manifold Learning

no code implementations • NeurIPS 2007 • Chinmay Hegde, Michael Wakin, Richard Baraniuk

First, we show that with a small number $M$ of {\em random projections} of sample points in $\reals^N$ belonging to an unknown $K$-dimensional Euclidean manifold, the intrinsic dimension (ID) of the sample set can be estimated to high accuracy.

Dimensionality Reduction