Graph embedding using tree edit-union

Jolliffe, 1986 Roweis, 2002, Non-linear dimensionality reduction by locally linear embedding, Science, 299, 2323 Tenenbaum, 2000, A global geometric framework for non-linear dimensionality reduction, Science, 290, 586, 10.1126/science.290.5500.2319 Belkin, 2003, Laplacian eigenmaps for dimensionality reduction and data representation, Neural Comput., 15, 1373, 10.1162/089976603321780317 Rizzi, 1998, Genetic operators for hierarchical graph clustering, Pattern Recognition Lett., 19, 1293, 10.1016/S0167-8655(98)00110-X J. Segen, Learning graph models of shape, in: J. Laird (Ed.), Proceedings of the Fifth International Conference on Machine Learning, 1988, pp. 29–25. Munger, 1999, Combinatorial search vs. genetic algorithms: a case study based on the generalized median graph problem, Pattern Recognition Lett., 20, 1271, 10.1016/S0167-8655(99)00094-X Wong, 1990 Bagdanov, 2003, First order Gaussian graphs for efficient structure classification, Pattern Recognition, 36, 1311, 10.1016/S0031-3203(02)00227-3 Heckerman, 1995, Learning Bayesian networks: the combination of knowledge and statistical data, Mach. Learn., 20, 197, 10.1007/BF00994016 M.A. Lozano, F. Escolano, ACM attributed graph clustering for learning classes of images, in: Graph Based Representations in Pattern Recognition, Lecture Notes in Computer Science, vol. 2726, 2003, pp. 247–258. H. Bunke, et al., Graph clustering using the weighted minimum common supergraph, in: Graph Based Representations in Pattern Recognition, Lecture Notes in Computer Science, vol. 2726, 2003, pp. 235–246. Jain, 2004, Central clustering of attributed graphs, Mach. Learn., 56, 169, 10.1023/B:MACH.0000033119.52532.ce B. Luo, A. Torsello, A. RoblesKelly, R.C. Wilson, E.R. Hancock, A probabilistic framework for graph clustering, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2001, pp. 912–919. X. Bai, E.R. Hancock, Heat kernels manifolds and graph embedding, in: Structural Syntactic and Statistical Pattern Recognition, Lecture Notes in Computer Science, vol. 3138, Springer, Berlin, 2004, pp. 198–206. Shi, 2000, Normalized cuts and image segmentation, IEEE Trans. Pattern Anal. Mach. Intell., 22, 888, 10.1109/34.868688 R. Kannan, et al., On clusterings: good, bad and spectral, FOCS 41, pp. 367–377. M. Pavan, M. Pelillo, Dominant sets and hierarchical clustering, in: Proceedings of the Ninth IEEE International Conference on Computer Vision, vol. I, 2003, pp. 362–369. Luo, 2002, Eigenspaces for graphs, Int. J. Image Graph., 2, 247, 10.1142/S0219467802000603 Luo, 2003, Spectral embedding of graphs, Pattern Recognition, 36, 2213, 10.1016/S0031-3203(03)00084-0 Wilson, 2005, Pattern vectors from algebraic graph theory, IEEE Trans. Pattern Anal. Mach. Intell., 27, 1112, 10.1109/TPAMI.2005.145 A. Shokoufandeh, S. Dickinson, K. Siddiqi, S. Zucker, Indexing using a spectral coding of topological structure, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 1999, pp. 491–497. Sengupta, 1995, Organizing large structural modelbases, IEEE Trans. Pattern Anal. Mach. Intell., 17, 321, 10.1109/34.385984 Sebastian, 2004, Recognition of shapes by editing their shock graphs, IEEE Trans. Pattern Anal. Mach. Intell., 26, 550, 10.1109/TPAMI.2004.1273924 Zhang, 1992, On the editing distance between unordered labeled trees, Inform. Process. Lett., 42, 133, 10.1016/0020-0190(92)90136-J A. Torsello, E.R. Hancock, Efficiently computing weighted tree edit distance using relaxation labeling, in: Energy Minimization Methods in Computer Vision and Pattern Recognition, 2001, pp. 438–453. Bunke, 2000, Mean and maximum common subgraph of two graphs, Pattern Recognition Lett., 21, 163, 10.1016/S0167-8655(99)00143-9 Siddiqi, 1999, Shock graphs and shape matching, Int. J. Comput. Vision, 35, 13, 10.1023/A:1008102926703 Torsello, 2004, A skeletal measure of 2D shape similarity, Comput. Vision Image Understanding, 95, 1, 10.1016/j.cviu.2004.03.006 Cox, 1994 Torsello, 2005, Polynomial-time metrics for attributed trees, IEEE Trans. Pattern Anal. Mach. Intell., 27, 1087, 10.1109/TPAMI.2005.146 P. Perona, W.T. Freeman, A factorization approach to grouping, in: European Conference on Computer Vision (ECCV), Lecture Notes in Computer Science, vol. 1406, 1998, pp. 655–670. Jain, 1988 Torsello, 2006, Learning shape-classes using a mixture of tree-unions, IEEE Trans. Pattern Anal. Mach. Intell., 28, 954, 10.1109/TPAMI.2006.125 Zhang, 1989, Simple fast algorithms for the editing distance between trees and related problems, SIAM J. Comput., 18, 1245, 10.1137/0218082