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Parallel & scalable zig-zag persistent homology
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.ORCID iD: 0000-0001-6322-7542
Jozef Stefan Institute. (AI Laboratory)
2012 (English)Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

By computing repeated pullbacks, we are able to compute zig-zag persistent homology in a way that easily parallelizes. In this paper, we demonstrate this algorithm together with its underlying mathematical foundation. We can parallelizeand scale the computation scheme.

Place, publisher, year, edition, pages
2012.
National Category
Computational Mathematics
Identifiers
URN: urn:nbn:se:kth:diva-107663OAI: oai:DiVA.org:kth-107663DiVA: diva2:576994
Conference
NIPS 2012 Workshop on Algebraic Topology and Machine Learning,December 7-8, 2012,Lake Tahoe, Nevada, United States
Funder
EU, FP7, Seventh Framework Programme, FP7-ICT-318493-STREP
Note

QC 20130116

Available from: 2013-01-16 Created: 2012-12-14 Last updated: 2013-01-16Bibliographically approved

Open Access in DiVA

fulltext(53 kB)266 downloads
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16f8716c7197dfc37a20470657aa6dc3ef747207ebc5cdf03568dddc9343011495d9d76e374aedd6555bb912b9a0ea7ebe7a28cb2dc5438f053fc13d64c42222
Type fulltextMimetype application/pdf

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Vejdemo-Johansson, Mikael

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
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More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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