@conference {cHaro07, title = {Stratification Learning: Detecting Mixed Density and Dimensionality in High Dimensional Point Clouds}, booktitle = {Neural Information Processing Systems NIPS}, year = {2007}, month = {12/2007}, publisher = {NIPS}, organization = {NIPS}, address = {Montreal}, 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.

}, author = {Haro, G. and Randall, Gregory and Sapiro, Guillermo} }