Spectral moments of random walks on s-walk dyadic conversions of hypergraphs are proposed as a whole-graph representation and achieve strong classification accuracy, though key theoretical bounds contain errors.
In: Fifth IEEE Inter- national Conference on Data Mining (ICDM’05)
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Representing Higher-Order Networks with Spectral Moments
Spectral moments of random walks on s-walk dyadic conversions of hypergraphs are proposed as a whole-graph representation and achieve strong classification accuracy, though key theoretical bounds contain errors.