A Fast Manifold Learning Algorithm for Dimensionality Reduction

This paper proposes a new manifold learning method called "Soinnmanifold". Traditional manifold learning method needs a lot of computation and appropriate priori parameters. This has somewhat restricted the domains in which manifold learning can potentially be applied. However, with the high-dimensional inputs, our method can generate a lowdimensional manifold in the high-dimensional space and determine the intrinsic dimension automatically. Then we will use this manifold to do dimensionality reduction quickly. Experiments demonstrate that our method can get promising results with less time and memory.