. Stratification Learning: Detecting Mixed Density and Dimensionality in High Dimensional Point Clouds. In Neural Information Processing Systems NIPS. Montreal: NIPS; 2007. 
(702.08 KB)
(702.08 KB) Abstract
The study of point cloud data sampled from a stratification, a collection of manifolds with possible different dimensions, is pursued in this paper. We present a technique for simultaneously soft clustering and estimating the mixed dimensionality and density of such structures. The framework is based on a maximum likelihood estimation of a Poisson mixture model. The presentation of the approach is completed with artificial and real examples demonstrating the importance of extending manifold learning to stratification learning.
