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Volumn , Issue , 2014, Pages 31-38

Distributed computation of persistent homology

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; EXPERIMENTS;

EID: 84916893505     PISSN: 21640300     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1137/1.9781611973198.4     Document Type: Conference Paper
Times cited : (136)

References (15)
  • 2
    • 84884335320 scopus 로고    scopus 로고
    • The compressed annotation matrix: An efficient data structure for computing persistent cohomology
    • H. L. Bodlaender and G. F. Italiano, editors, Springer Berlin Heidelberg
    • J.-D. Boissonnat, T. K. Dey, and C. Maria. The compressed annotation matrix: An efficient data structure for computing persistent cohomology. In H. L. Bodlaender and G. F. Italiano, editors, Algorithms - ESA 2013, volume 8125 of Lecture Notes in Computer Science, pages 695-706. Springer Berlin Heidelberg, 2013.
    • (2013) Algorithms - ESA 2013, Volume 8125 of Lecture Notes in Computer Science , pp. 695-706
    • Boissonnat, J.-D.1    Dey, T.K.2    Maria, C.3
  • 4
    • 84992504901 scopus 로고    scopus 로고
    • An output-sensitive algorithm for persistent homology
    • C. Chen and M. Kerber. An output-sensitive algorithm for persistent homology. Computational Geometry, 46(4):435-447, 2013.
    • (2013) Computational Geometry , vol.46 , Issue.4 , pp. 435-447
    • Chen, C.1    Kerber, M.2
  • 13
    • 78149252299 scopus 로고    scopus 로고
    • Persistence algorithm takes cubic time in the worst case
    • Durham, NC
    • D. Morozov. Persistence algorithm takes cubic time in the worst case. In BioGeometry News. Duke Computer Science, Durham, NC, 2005.
    • (2005) BioGeometry News. Duke Computer Science
    • Morozov, D.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.