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2014 Fall Colloquium: "Clustering Tree-Structure Data on Manifold"

December 04, 2014
Helen Wood Hall - 1W501 Classroom

Hongyu Miao

Department of Biostatistics and Computational Biology
University of Rochester School of Medicine and Dentistry
2014 Fall Colloquium
Hongyu Miao, PhD
Assistant Professor
Department of Biostatistics and Computational Biology
University of Rochester
Clustering Tree-structured Data on Manifold
Thursday, December 4, 2014
3:30 P.M. – 5:00 p.m.
Helen Wood Hall – 1W501 Classroom


Tree-structured data usually contain both topological and geometrical information, and are necessarily considered on manifold instead of Euclidean space for appropriate data parameterization and analysis. In this study, we propose a novel tree-structured data parameterization, called Topology-Attribute matrix (T-A matrix), so the data clustering task can be conducted on matrix manifold. We incorporate the structure constraints embedded in data into the negative matrix factorization method to determine meta-trees from the T-A matrix, and the signature vector of each single tree can then be extracted by meta-tree decomposition. The meta-tree space turns out to be a cone space, in which we explore the distance metric and implement the clustering algorithm based on the concepts like Fréchet mean. Finally, the T-A matrix based clustering (TAMBAC) framework is evaluated and compared using both simulated data and real retinal images to illustrate its efficiency and accuracy. 

Category: Talks