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  • Source: Applied Soft Computing. Unidade: ICMC

    Subjects: APRENDIZADO COMPUTACIONAL, COMPONENTES PRINCIPAIS

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    • ABNT

      HORVÁTH, Tomás e MANTOVANI, Rafael Gomes e CARVALHO, André Carlos Ponce de Leon Ferreira de. Hyper-parameter initialization of classification algorithms using dynamic time warping: a perspective on PCA meta-features. Applied Soft Computing, v. 134, p. 1-17, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.asoc.2022.109969. Acesso em: 13 out. 2024.
    • APA

      Horváth, T., Mantovani, R. G., & Carvalho, A. C. P. de L. F. de. (2023). Hyper-parameter initialization of classification algorithms using dynamic time warping: a perspective on PCA meta-features. Applied Soft Computing, 134, 1-17. doi:10.1016/j.asoc.2022.109969
    • NLM

      Horváth T, Mantovani RG, Carvalho ACP de LF de. Hyper-parameter initialization of classification algorithms using dynamic time warping: a perspective on PCA meta-features [Internet]. Applied Soft Computing. 2023 ; 134 1-17.[citado 2024 out. 13 ] Available from: https://doi.org/10.1016/j.asoc.2022.109969
    • Vancouver

      Horváth T, Mantovani RG, Carvalho ACP de LF de. Hyper-parameter initialization of classification algorithms using dynamic time warping: a perspective on PCA meta-features [Internet]. Applied Soft Computing. 2023 ; 134 1-17.[citado 2024 out. 13 ] Available from: https://doi.org/10.1016/j.asoc.2022.109969
  • Source: Lecture Notes in Computer Science. Conference titles: International Conference on Intelligent Data Engineering and Automated Learning - IDEAL. Unidade: ICMC

    Subjects: APRENDIZADO COMPUTACIONAL, COMPONENTES PRINCIPAIS, ANÁLISE DE SÉRIES TEMPORAIS

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    • ABNT

      HORVÁTH, Tomás e MANTOVANI, Rafael Gomes e CARVALHO, André Carlos Ponce de Leon Ferreira de. Time-series in hyper-parameter initialization of machine learning techniques. Lecture Notes in Computer Science. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-91608-4_25. Acesso em: 13 out. 2024. , 2021
    • APA

      Horváth, T., Mantovani, R. G., & Carvalho, A. C. P. de L. F. de. (2021). Time-series in hyper-parameter initialization of machine learning techniques. Lecture Notes in Computer Science. Cham: Springer. doi:10.1007/978-3-030-91608-4_25
    • NLM

      Horváth T, Mantovani RG, Carvalho ACP de LF de. Time-series in hyper-parameter initialization of machine learning techniques [Internet]. Lecture Notes in Computer Science. 2021 ; 13113 246-258.[citado 2024 out. 13 ] Available from: https://doi.org/10.1007/978-3-030-91608-4_25
    • Vancouver

      Horváth T, Mantovani RG, Carvalho ACP de LF de. Time-series in hyper-parameter initialization of machine learning techniques [Internet]. Lecture Notes in Computer Science. 2021 ; 13113 246-258.[citado 2024 out. 13 ] Available from: https://doi.org/10.1007/978-3-030-91608-4_25
  • Source: Physical Review E. Unidade: ICMC

    Subjects: REDES COMPLEXAS, TEORIA DOS GRAFOS, PROBABILIDADE

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    • ABNT

      MÉNDEZ-BERMÚDEZ, J. A et al. Universality in the spectral and eigenfunction properties of random networks. Physical Review E, v. 91, n. 3, p. 032122-1-032122-10, 2015Tradução . . Disponível em: https://doi.org/10.1103/PhysRevE.91.032122. Acesso em: 13 out. 2024.
    • APA

      Méndez-Bermúdez, J. A., Alcazar-López, A., Martínez-Mendoza, A. J., Rodrigues, F. A., & Peron, T. (2015). Universality in the spectral and eigenfunction properties of random networks. Physical Review E, 91( 3), 032122-1-032122-10. doi:10.1103/PhysRevE.91.032122
    • NLM

      Méndez-Bermúdez JA, Alcazar-López A, Martínez-Mendoza AJ, Rodrigues FA, Peron T. Universality in the spectral and eigenfunction properties of random networks [Internet]. Physical Review E. 2015 ; 91( 3): 032122-1-032122-10.[citado 2024 out. 13 ] Available from: https://doi.org/10.1103/PhysRevE.91.032122
    • Vancouver

      Méndez-Bermúdez JA, Alcazar-López A, Martínez-Mendoza AJ, Rodrigues FA, Peron T. Universality in the spectral and eigenfunction properties of random networks [Internet]. Physical Review E. 2015 ; 91( 3): 032122-1-032122-10.[citado 2024 out. 13 ] Available from: https://doi.org/10.1103/PhysRevE.91.032122

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