Abstract
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.
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Lang, K.J., Mahoney, M.W., Orecchia, L. (2009). Empirical Evaluation of Graph Partitioning Using Spectral Embeddings and Flow. In: Vahrenhold, J. (eds) Experimental Algorithms. SEA 2009. Lecture Notes in Computer Science, vol 5526. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02011-7_19
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DOI: https://doi.org/10.1007/978-3-642-02011-7_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02010-0
Online ISBN: 978-3-642-02011-7
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