S. Guattery and G. L. Miller. On the quality of spectral separators. SIAM Journal on Matrix Analysis and Applications, 19(3):701-719, 1998. Home/Search Document Details and Download
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A Min-max Cut Algorithm for Graph Partitioning and Data.. - Ding, He, Zha, Gu, Simon (2001) (3 citations) (Correct)
....clustering accuracy due to linkage based re nements for Mcut alone, Mcut plus swap, and Mcut plus swap and move over 5 smallest on both sides of the cutpoint. 9 Linkage di erential order the best known linearized order to search for the optimal cut (although delicate counter examples exist [13, 23]) Is there a linear search order better than the Fiedler order Our analysis in previous sections suggests a new linear search order. Given the linkage di erence in Figure 2, we see that quite a few nodes far away from the cut point have wrong signs, that is, they belong to the other ....
S. Guattery and G. L. Miller. On the quality of spectral separators. SIAM Journal of Matrix Anal. Appl., 19(3), 1998.
New Graph Partitioning Algorithms - Holzrichter, Oliveira (1998) (Correct)
....by using the third and fourth smallest eigenpairs of the graph Laplacian. Spielman and Teng [29] present an upper bound on the Fiedler value of bounded degree d dimensional graphs, and they relate this upper bound to the number of edges cut by a Fiedler cut. In contrast, Guattery and Miller [14] present graphs for which spectral partitioning yields poor separators. Simon and Teng [28] show that p way partitions produced by recursive bisection can yield far from optimal partitions, even when an optimal partitioning algorithm is used. Computing the Fiedler vector can be time consuming. ....
S. Guattery and G. L. Miller. On the quality of spectral separators. SIAM Journal on Matrix Analysis and Applications, 19:701--719. 18
A Graph Based Method for Generating the Fiedler Vector of.. - Holzrichter, Oliveira (Correct)
....has shown how finding a partition of a graph which minimizes the number of edges cut can be transformed into an eigenvalue problem involving the graph Laplacian. This is the foundation of spectral methods. Theory exists to show the effectiveness of this approach. The work of Guattery and Miller [7] present examples of graphs for which spectral partitioning does not work well. Nevertheless, spectral partition methods work well on boundeddegree planar graphs and finite element meshes [17] Chan et al. 3] show that spectral partitioning is optimal in the sense that the partition vector ....
S. Guattery and G. L. Miller. On the quality of spectral separators. SIAM Journal on Matrix Analysis and Applications, 19:701--719, 1998. M. Holzrichter and S. Oliveira
The Path Resistance Method for Bounding the Smallest.. - Guattery, Leighton.. (1993) Self-citation (Guattery) (Correct)
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Guattery, S. and Miller, G. L. (1998) On the quality of spectral separators. SIAM Journal on Matrix Analysis and Applications 19(3) 701-719 (July).
Graph Embeddings and Laplacian Eigenvalues - Guattery, Miller (2000) Self-citation (Guattery Miller) (Correct)
.... of the connection between Laplacian spectra (particularly with respect to # 2 ) and properties of the associated graphs dates back to Fiedler s work in the 1970s (see, e.g. 10] and [11] These properties have been used in graph algorithms, particularly algorithms for finding small separators [17, 25, 28]. The relationship between graph embeddings and matrix representations has been GRAPH EMBEDDINGS AND LAPLACIAN EIGENVALUES 705 the subject of much interesting research. A large proportion of this work has been aimed at bounding the second largest eigenvalues of time reversible Markov chains in ....
S. Guattery and G. L. Miller, On the quality of spectral separators, SIAM J. Matrix Anal. Appl., 19 (1998), pp. 701--719.
Graph Embeddings and Laplacian Eigenvalues - Guattery, Miller (1998) Self-citation (Guattery Miller) (Correct)
.... of the connection between Laplacian spectra (particularly with respect to # 2 ) and properties of the associated graphs dates back to Fiedler s work in the 1970 s (see, e.g. 10] and [11] These properties have been used in graph algorithms, particularly algorithms for finding small separators [17, 25, 28]. The relationship between graph embeddings and matrix representations has been the subject of much interesting research. A large proportion of this work has been aimed at bounding the second largest eigenvalues of time reversible Markov chains in order to bound the mixing time for random walks. ....
S. Guattery and G. L. Miller, On the quality of spectral separators, SIAM J. Mat. Anal. App., (1997). To appear.
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S. Guattery and G. L. Miller. On the quality of spectral separators. SIAM Journal on Matrix Analysis and Applications, 19(3):701-719, 1998.
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S. Guattery and G. L. Miller. On the quality of spectral separators. SIAM Journal on Matrix Analysis and Applications, 19(3):701-719, 1998.
On Semidefinite Relaxations for Normalized k-Cut and.. - Xing, Jordan (2003) (Correct)
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S. Guattery and G. L. Miller. On the quality of spectral separators. SIAM Journal on Matrix Analysis and Applications, 19(3):701-719, 1998.
Efficient Algorithms for Sampling and Clustering of Large.. - Orponen, Schaeffer (Correct)
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S. Guattery and G. L. Miller. On the quality of spectral separators. SIAM Journal on Matrix Analysis and Applications, 19(3):701--719, 1998.
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