Menu

Filtros : "high-dimensional data" Limpar

Filtros

Refine with date range

  • 1

1 - 2 (2 records)

  • Artigo de periodico

    Getting over high-dimensionality: how multidimensional projection methods can assist data science (2022)

    Ortigossa, Evandro Scudeleti ; Dias, Fabio Felix ; Nascimento, Diego Carvalho do

    Source: Applied Sciences. Unidade: ICMC

    Subjects: DESCOBERTA DE CONHECIMENTO, VISUALIZAÇÃO

    Versão PublicadaAcesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas

    • ABNT

      ORTIGOSSA, Evandro Scudeleti e DIAS, Fabio Felix e NASCIMENTO, Diego Carvalho do. Getting over high-dimensionality: how multidimensional projection methods can assist data science. Applied Sciences, v. 12, n. 13, p. 1-36, 2022Tradução . . Disponível em: https://doi.org/10.3390/app12136799. Acesso em: 23 jan. 2026.

    • APA

      Ortigossa, E. S., Dias, F. F., & Nascimento, D. C. do. (2022). Getting over high-dimensionality: how multidimensional projection methods can assist data science. Applied Sciences, 12( 13), 1-36. doi:10.3390/app12136799

    • NLM

      Ortigossa ES, Dias FF, Nascimento DC do. Getting over high-dimensionality: how multidimensional projection methods can assist data science [Internet]. Applied Sciences. 2022 ; 12( 13): 1-36.[citado 2026 jan. 23 ] Available from: https://doi.org/10.3390/app12136799

    • Vancouver

      Ortigossa ES, Dias FF, Nascimento DC do. Getting over high-dimensionality: how multidimensional projection methods can assist data science [Internet]. Applied Sciences. 2022 ; 12( 13): 1-36.[citado 2026 jan. 23 ] Available from: https://doi.org/10.3390/app12136799

  • Artigo de periodico

    TopoMap: a 0-dimensional homology preserving projection of high-dimensional data (2021)

    Doraiswamy, Harish ; Tierny, Julien ; Silva, Paulo J. S. ; Nonato, Luis Gustavo ; Silva, Claudio

    Source: IEEE Transactions on Visualization and Computer Graphics. Unidade: ICMC

    Subjects: TOPOLOGIA, ANÁLISE DE DADOS, PROJEÇÃO

    PrivadoAcesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas

    • ABNT

      DORAISWAMY, Harish et al. TopoMap: a 0-dimensional homology preserving projection of high-dimensional data. IEEE Transactions on Visualization and Computer Graphics, v. 27, n. 2, p. 561-571, 2021Tradução . . Disponível em: https://doi.org/10.1109/TVCG.2020.3030441. Acesso em: 23 jan. 2026.

    • APA

      Doraiswamy, H., Tierny, J., Silva, P. J. S., Nonato, L. G., & Silva, C. (2021). TopoMap: a 0-dimensional homology preserving projection of high-dimensional data. IEEE Transactions on Visualization and Computer Graphics, 27( 2), 561-571. doi:10.1109/TVCG.2020.3030441

    • NLM

      Doraiswamy H, Tierny J, Silva PJS, Nonato LG, Silva C. TopoMap: a 0-dimensional homology preserving projection of high-dimensional data [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2021 ; 27( 2): 561-571.[citado 2026 jan. 23 ] Available from: https://doi.org/10.1109/TVCG.2020.3030441

    • Vancouver

      Doraiswamy H, Tierny J, Silva PJS, Nonato LG, Silva C. TopoMap: a 0-dimensional homology preserving projection of high-dimensional data [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2021 ; 27( 2): 561-571.[citado 2026 jan. 23 ] Available from: https://doi.org/10.1109/TVCG.2020.3030441
  • 1

1 - 2 (2 records)

Digital Library of Intellectual Production of Universidade de São Paulo     2012 - 2026