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Monte carlo techniques for estimating the fiedler vector in graph applications

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2002) 2330 LNCS(PART 2) 635-645
DOI: 10.1007/3-540-46080-2_66
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Abstract

Determiningthe Fiedler vector of the Laplacian or adjacency matrices of graphs is the most computationally intensive component of several applications, such as graph partitioning, graph coloring, envelope reduction, and seriation. Often an approximation of the Fiedler vector is sufficient.We discuss issues involved in the use of Monte Carlo techniques for this purpose. © Springer-Verlag Berlin Heidelberg 2002.

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APA

Srinivasan, A., & Mascagni, M. (2002). Monte carlo techniques for estimating the fiedler vector in graph applications. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2330 LNCS, pp. 635–645). Springer Verlag. https://doi.org/10.1007/3-540-46080-2_66

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