Adaptive aggregation on graphs

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


We generalize some of the functional (hypercircle) a posteriori estimates from finite element settings to general graphs or Hilbert space settings. Several theoretical results in regard to the generalized a posteriori error estimators are provided. We use these estimates to construct aggregation based coarse spaces for graph Laplacians. The estimator is used to assess the quality of an aggregation adaptively. Furthermore, a reshaping based algorithm is tested on several numerical examples.

Original languageEnglish (US)
Pages (from-to)718-730
Number of pages13
JournalJournal of Computational and Applied Mathematics
StatePublished - Oct 1 2018

All Science Journal Classification (ASJC) codes

  • Computational Mathematics
  • Applied Mathematics


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