Sylvester Tensor Equation for Multi-Way Association

Boxin Du, Lihui Liu, Hanghang Tong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

How can we identify the same or similar users from a collection of social network platforms (e.g., Facebook, Twitter, LinkedIn, etc.)? Which restaurant shall we recommend to a given user at the right time at the right location? Given a disease, which genes and drugs are most relevant? Multi-way association, which identifies strongly correlated node sets from multiple input networks, is the key to answering these questions. Despite its importance, very few multi-way association methods exist due to its high complexity. In this paper, we formulate multi-way association as a convex optimization problem, whose optimal solution can be obtained by a Sylvester tensor equation. Furthermore, we propose two fast algorithms to solve the Sylvester tensor equation, with a linear time and space complexity. We further provide theoretic analysis in terms of the sensitivity of the Sylvester tensor equation solution. Empirical evaluations demonstrate the efficacy of the proposed method.

Original languageEnglish (US)
Title of host publicationKDD 2021 - Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
PublisherAssociation for Computing Machinery
Pages311-321
Number of pages11
ISBN (Electronic)9781450383325
DOIs
StatePublished - Aug 14 2021
Event27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2021 - Virtual, Online, Singapore
Duration: Aug 14 2021Aug 18 2021

Publication series

NameProceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Conference

Conference27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2021
Country/TerritorySingapore
CityVirtual, Online
Period8/14/218/18/21

Keywords

  • graph mining
  • multi-network mining
  • multi-way association
  • sylvester tensor equation

ASJC Scopus subject areas

  • Software
  • Information Systems

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