Graph Drawing via Gradient Descent, (GD)2

Reyan Ahmed, Felice De Luca, Sabin Devkota, Stephen Kobourov, Mingwei Li

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

Abstract

Readability criteria, such as distance or neighborhood preservation, are often used to optimize node-link representations of graphs to enable the comprehension of the underlying data. With few exceptions, graph drawing algorithms typically optimize one such criterion, usually at the expense of others. We propose a layout approach, Graph Drawing via Gradient Descent, (GD)2, that can handle multiple readability criteria. (GD)2 can optimize any criterion that can be described by a smooth function. If the criterion cannot be captured by a smooth function, a non-smooth function for the criterion is combined with another smooth function, or auto-differentiation tools are used for the optimization. Our approach is flexible and can be used to optimize several criteria that have already been considered earlier (e.g., obtaining ideal edge lengths, stress, neighborhood preservation) as well as other criteria which have not yet been explicitly optimized in such fashion (e.g., vertex resolution, angular resolution, aspect ratio). We provide quantitative and qualitative evidence of the effectiveness of (GD)2 with experimental data and a functional prototype: http://hdc.cs.arizona.edu/~mwli/graph-drawing/.

Original languageEnglish (US)
Title of host publicationGraph Drawing and Network Visualization - 28th International Symposium, GD 2020, Revised Selected Papers
EditorsDavid Auber, Pavel Valtr
PublisherSpringer Science and Business Media Deutschland GmbH
Pages3-17
Number of pages15
ISBN (Print)9783030687656
DOIs
StatePublished - 2020
Event28th International Symposium on Graph Drawing and Network Visualization, GD 2020 - Virtual, Online
Duration: Sep 16 2020Sep 18 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12590 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference28th International Symposium on Graph Drawing and Network Visualization, GD 2020
CityVirtual, Online
Period9/16/209/18/20

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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