License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.ICALP.2018.159
URN: urn:nbn:de:0030-drops-91639
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2018/9163/
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Mallmann-Trenn, Frederik ; Musco, Cameron ; Musco, Christopher

Eigenvector Computation and Community Detection in Asynchronous Gossip Models

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Abstract

We give a simple distributed algorithm for computing adjacency matrix eigenvectors for the communication graph in an asynchronous gossip model. We show how to use this algorithm to give state-of-the-art asynchronous community detection algorithms when the communication graph is drawn from the well-studied stochastic block model. Our methods also apply to a natural alternative model of randomized communication, where nodes within a community communicate more frequently than nodes in different communities.
Our analysis simplifies and generalizes prior work by forging a connection between asynchronous eigenvector computation and Oja's algorithm for streaming principal component analysis. We hope that our work serves as a starting point for building further connections between the analysis of stochastic iterative methods, like Oja's algorithm, and work on asynchronous and gossip-type algorithms for distributed computation.

BibTeX - Entry

@InProceedings{mallmanntrenn_et_al:LIPIcs:2018:9163,
  author =	{Frederik Mallmann-Trenn and Cameron Musco and Christopher Musco},
  title =	{{Eigenvector Computation and Community Detection in Asynchronous Gossip Models}},
  booktitle =	{45th International Colloquium on Automata, Languages, and  Programming (ICALP 2018)},
  pages =	{159:1--159:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-076-7},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{107},
  editor =	{Ioannis Chatzigiannakis and Christos Kaklamanis and D{\'a}niel Marx and Donald Sannella},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2018/9163},
  URN =		{urn:nbn:de:0030-drops-91639},
  doi =		{10.4230/LIPIcs.ICALP.2018.159},
  annote =	{Keywords: block model, community detection, distributed clustering, eigenvector computation, gossip algorithms, population protocols}
}

Keywords: block model, community detection, distributed clustering, eigenvector computation, gossip algorithms, population protocols
Collection: 45th International Colloquium on Automata, Languages, and Programming (ICALP 2018)
Issue Date: 2018
Date of publication: 04.07.2018

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