Incremental Hessian Locally Linear Embedding algorithm

In this paper we propose an incremental version of Hessian locally linear embedding (HLLE) on the basis of incremental locally linear embedding (LLE) generalizations. The main idea behind our algorithm is to produce a lower dimension representation of a high-dimensional manifold such that the significant characteristics of the dataset are preserved while adapting to newly added points arriving to the dataset. Our experimental results verify how the new projection of points, along with the additional points, produces a good fit to the original manifold.