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Spectrally Robust Graph Isomorphism

Authors Alexandra Kolla, Ioannis Koutis, Vivek Madan, Ali Kemal Sinop

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LIPIcs.ICALP.2018.84.pdf
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Author Details

Alexandra Kolla
  • Department of Computer Science, University of Colorado at Boulder
Ioannis Koutis
  • Department of Computer Science, New Jersey Institute of Technology
Vivek Madan
  • Department of Computer Science, University of Illinois, Urbana-Champaign
Ali Kemal Sinop
  • TOBB University of Economics and Technology, Ankara, Turkey

Funding

  • Kolla, Alexandra: Supported by NSF CAREER grant CCF-1452923.
  • Koutis, Ioannis: Supported by NSF CAREER grant CCF-1319376.

Cite AsGet BibTex

Alexandra Kolla, Ioannis Koutis, Vivek Madan, and Ali Kemal Sinop. Spectrally Robust Graph Isomorphism. In 45th International Colloquium on Automata, Languages, and Programming (ICALP 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 107, pp. 84:1-84:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
https://doi.org/10.4230/LIPIcs.ICALP.2018.84

Abstract

We initiate the study of spectral generalizations of the graph isomorphism problem. b) The Spectral Graph Dominance (SGD) problem: On input of two graphs G and H does there exist a permutation pi such that G preceq pi(H)? c) The Spectrally Robust Graph Isomorphism (kappa-SRGI) problem: On input of two graphs G and H, find the smallest number kappa over all permutations pi such that pi(H) preceq G preceq kappa c pi(H) for some c. SRGI is a natural formulation of the network alignment problem that has various applications, most notably in computational biology. G preceq c H means that for all vectors x we have x^T L_G x <= c x^T L_H x, where L_G is the Laplacian G. We prove NP-hardness for SGD. We also present a kappa^3-approximation algorithm for SRGI for the case when both G and H are bounded-degree trees. The algorithm runs in polynomial time when kappa is a constant.

Subject Classification

ACM Subject Classification
  • Mathematics of computing → Graph algorithms
Keywords
  • Network Alignment
  • Graph Isomorphism
  • Graph Similarity

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