2009 | OriginalPaper | Buchkapitel
Empirical Evaluation of Graph Partitioning Using Spectral Embeddings and Flow
verfasst von : Kevin J. Lang, Michael W. Mahoney, Lorenzo Orecchia
Erschienen in: Experimental Algorithms
Verlag: Springer Berlin Heidelberg
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We present initial results from the first empirical evaluation of a graph partitioning algorithm inspired by the Arora-Rao-Vazirani algorithm of [5], which combines spectral and flow methods in a novel way. We have studied the parameter space of this new algorithm,
e.g.
, examining the extent to which different parameter settings interpolate between a more spectral and a more flow-based approach, and we have compared results of this algorithm to results from previously known and optimized algorithms such as
Metis
.