Intersection and convex combination in multi-source spectral planted cluster detection

Rajmonda S. Caceres, Steven T. Smith, Benjamin A. Miller

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Planted cluster detection is an important form of signal detection when the data are in the form of a graph. When there are multiple graphs representing multiple connection types, the method of aggregation can have significant impact on the results of a detection algorithm. This paper addresses the tradeoff between two possible aggregation methods: convex combination and intersection. For a spectral detection method, convex combination dominates when the cluster is relatively sparse in at least one graph, while the intersection method dominates in cases where it is dense across graphs. Experimental results confirm the theory. We consider the context of adversarial cluster placement, and determine how an adversary would distribute connections among the graphs to best avoid detection.

Original languageEnglish
Title of host publication2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages365-369
Number of pages5
ISBN (Electronic)9781509045457
DOIs
StatePublished - 19 Apr 2017
Externally publishedYes
Event2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Washington, United States
Duration: 7 Dec 20169 Dec 2016

Publication series

Name2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings

Conference

Conference2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016
Country/TerritoryUnited States
CityWashington
Period7/12/169/12/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

  • Community detection
  • Graph aggregation
  • Graph analysis
  • Multi-source networks
  • Planted cluster detection

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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