A Theoretical Framework of the Graph Shift Algorithm

Authors

  • Xuhui Fan University of Technology, Sydney
  • Longbing Cao University of Technology, Sydney

DOI:

https://doi.org/10.1609/aaai.v26i1.8410

Keywords:

Convergence, Graph Shift, Zangwill

Abstract

Since no theoretical foundations for proving the convergence of Graph Shift Algorithm have been reported, we provide a generic framework consisting of three key GS components to fit the Zangwill’s convergence theorem. We show that the sequence set generated by the GS procedures always terminates at a local maximum, or at worst, contains a subsequence which converges to a local maximum of the similarity measure function. What is more, a theoretical framework is proposed to apply our proof to a more general case.

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Published

2021-09-20

How to Cite

Fan, X., & Cao, L. (2021). A Theoretical Framework of the Graph Shift Algorithm. Proceedings of the AAAI Conference on Artificial Intelligence, 26(1), 2419-2420. https://doi.org/10.1609/aaai.v26i1.8410