Riemannian Manifold

Semi-supervised optimization algorithm basedon Laplacian Eigenmaps

“…The dimensionality reduction method based on eigenvalues is also known as the Manifold Learning algorithm. The dimensionality reduction algorithm of manifold learning was first proposed by ST Roweis and JB Tenenbaum, and it has gradually become a research hotspot of data dimensionality reduction [16]. This type of method assumes that the high-dimensional data is distributed on an essentially low-dimensional nonlinear manifold.…”