A spectral approach to learning structural variations in graphs

Bin Luo, Richard C. Wilson, Edwin R. Hancock
2006 Pattern Recognition  
This paper shows how to construct a linear deformable model for graph structure by performing principal components analysis (PCA) on the vectorised adjacency matrix. We commence by using correspondence information to place the nodes of each of a set of graphs in a standard reference order. Using the correspondences order, we convert the adjacency matrices to long-vectors and compute the long-vector covariance matrix. By projecting the vectorised adjacency matrices onto the leading eigenvectors
more » ... f the covariance matrix, we embed the graphs in a pattern-space. We illustrate the utility of the resulting method for shape-analysis.
doi:10.1016/j.patcog.2006.01.001 fatcat:cg25sm4xbzen7oe4g5smd4c5gq