Empirical Evaluation of Graph Partitioning Using Spectral Embeddings and Flow

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.

• Type: Conference
• Year: 2009
• Where: WEA
• Authors: Kevin J. Lang, Michael W. Mahoney, Lorenzo Orecchia
• Keywords: Arora-Rao-Vazirani Algorithm, Graph Partitioning Algorithm, WEA 2009, first Empirical Evaluation