Skip Navigation
York U: Redefine the PossibleHOME | Current Students | Faculty & Staff | Research | International
Search »FacultiesLibrariesCampus MapsYork U OrganizationDirectorySite Index
Future Students, Alumni & Visitors
2003 Technical Reports

Clustering on Unobserved Data using Mixture of Gaussians

Lu Ye and Minas E. Spetsakis

Technical Report CS-2003-08

York University

October 6, 2003

Abstract

This report provides an review of Clustering using Mixture Models and the Expectation Maximization method and then extends these concepts to the problem of clustering of unobserved data where we cluster a set of vectors u_i for i = 1 .. N for which we only know the probability distribution. This problem has several applications in Computer Vision where we want to cluster noisy data.

Download paper in PDF format.



The documents distributed by this server have been provided by the contributing authors as a means to ensure timely dissemination of scholarly and technical work on a noncommercial basis. Copyright and all rights therein are maintained by the authors or by other copyright holders, notwithstanding that they have offered their works here electronically. It is understood that all persons copying this information will adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.