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  • Artigo de periodico

    TopoMap++: a faster and more space efficient technique to compute projections with topological guarantees (2025)

    Guardieiro, Vitoria ; Oliveira, Felipe Inagaki de ; Doraiswamy, Harish ; Nonato, Luis Gustavo ; Silva, Claudio

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

    Subjects: ANÁLISE DE DADOS, TOPOLOGIA, PROJEÇÃO

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

    • ABNT

      GUARDIEIRO, Vitoria et al. TopoMap++: a faster and more space efficient technique to compute projections with topological guarantees. IEEE Transactions on Visualization and Computer Graphics, v. 31, n. 1, p. 229-239, 2025Tradução . . Disponível em: https://doi.org/10.1109/TVCG.2024.3456365. Acesso em: 25 jan. 2026.

    • APA

      Guardieiro, V., Oliveira, F. I. de, Doraiswamy, H., Nonato, L. G., & Silva, C. (2025). TopoMap++: a faster and more space efficient technique to compute projections with topological guarantees. IEEE Transactions on Visualization and Computer Graphics, 31( 1), 229-239. doi:10.1109/TVCG.2024.3456365

    • NLM

      Guardieiro V, Oliveira FI de, Doraiswamy H, Nonato LG, Silva C. TopoMap++: a faster and more space efficient technique to compute projections with topological guarantees [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2025 ; 31( 1): 229-239.[citado 2026 jan. 25 ] Available from: https://doi.org/10.1109/TVCG.2024.3456365

    • Vancouver

      Guardieiro V, Oliveira FI de, Doraiswamy H, Nonato LG, Silva C. TopoMap++: a faster and more space efficient technique to compute projections with topological guarantees [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2025 ; 31( 1): 229-239.[citado 2026 jan. 25 ] Available from: https://doi.org/10.1109/TVCG.2024.3456365

  • Trabalho de evento-anais periodico

    Effective sample size, dimensionality, and generalization in covariate shift adaptation (2023)

    Polo, Felipe Maia ; Vicente, Renato

    Source: Neural Computing and Applications. Conference titles: LatinX in AI at NeurIPS. Unidade: IME

    Assunto: MATEMÁTICA APLICADA

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

    • ABNT

      POLO, Felipe Maia e VICENTE, Renato. Effective sample size, dimensionality, and generalization in covariate shift adaptation. Neural Computing and Applications. Godalming: Instituto de Matemática e Estatística, Universidade de São Paulo. Disponível em: https://doi.org/10.1007/s00521-021-06615-1. Acesso em: 25 jan. 2026. , 2023

    • APA

      Polo, F. M., & Vicente, R. (2023). Effective sample size, dimensionality, and generalization in covariate shift adaptation. Neural Computing and Applications. Godalming: Instituto de Matemática e Estatística, Universidade de São Paulo. doi:10.1007/s00521-021-06615-1

    • NLM

      Polo FM, Vicente R. Effective sample size, dimensionality, and generalization in covariate shift adaptation [Internet]. Neural Computing and Applications. 2023 ; 35( 25): 18187-18199.[citado 2026 jan. 25 ] Available from: https://doi.org/10.1007/s00521-021-06615-1

    • Vancouver

      Polo FM, Vicente R. Effective sample size, dimensionality, and generalization in covariate shift adaptation [Internet]. Neural Computing and Applications. 2023 ; 35( 25): 18187-18199.[citado 2026 jan. 25 ] Available from: https://doi.org/10.1007/s00521-021-06615-1
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