Geometric Manifold Energy and Manifold Clustering

Authors:
Hongyu Li;Qiyong Guo;Jinyuan Jia;Jussi Parkkinen
Affiliations:
School of Software Engineering, Tongji University, Shanghai, China and Department of Computer Science and Statistics, University of Joensuu, Joensuu, Finland;Department of Computer Science and Engineering, Fudan University, Shanghai, China;School of Software Engineering, Tongji University, Shanghai, China;Department of Computer Science and Statistics, University of Joensuu, Joensuu, Finland
Venue:
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
Year:
2009

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Abstract

A general nonparametric technique is proposed for the description of geometric manifold energy of unorganized data. Minimizing the energy leads to an optimal cycle, from which underlying manifolds are easily distinguished. We design a new framework for manifold clustering based on energy minimization. In addition, we propose the active tabu search method to approximately solve for the optimal solution to energy minimization. We have applied the proposed technique to both synthetic and real data. Experimental results show that the method is feasible and promising in manifold clustering.