A metrics-oriented architectural model to characterize complexity on machine learning-enabled systems (2025)
- Autor:
- Autor USP: FERREIRA, RENATO CORDEIRO - IME
- Unidade: IME
- Sigla do Departamento: MAC
- DOI: 10.1109/CAIN66642.2025.00041
- Subjects: APRENDIZADO COMPUTACIONAL; ARQUITETURA E ORGANIZAÇÃO DE COMPUTADORES; MÉTRICAS DE SOFTWARE
- Language: Inglês
- Imprenta:
- Publisher: IEEE
- Publisher place: Piscataway
- Date published: 2025
- Source:
- Volume/Número/Paginação/Ano: p. 256-260, 2025
- Conference titles: IEEE/ACM International Conference on AI Engineering - Software Engineering for AI - CAIN
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: green
-
ABNT
FERREIRA, Renato Cordeiro. A metrics-oriented architectural model to characterize complexity on machine learning-enabled systems. 2025, Anais.. Piscataway: IEEE, 2025. p. 256-260. Disponível em: https://doi.org/10.1109/CAIN66642.2025.00041. Acesso em: 30 dez. 2025. -
APA
Ferreira, R. C. (2025). A metrics-oriented architectural model to characterize complexity on machine learning-enabled systems. In (p. 256-260). Piscataway: IEEE. doi:10.1109/CAIN66642.2025.00041 -
NLM
Ferreira RC. A metrics-oriented architectural model to characterize complexity on machine learning-enabled systems [Internet]. 2025 ; 256-260.[citado 2025 dez. 30 ] Available from: https://doi.org/10.1109/CAIN66642.2025.00041 -
Vancouver
Ferreira RC. A metrics-oriented architectural model to characterize complexity on machine learning-enabled systems [Internet]. 2025 ; 256-260.[citado 2025 dez. 30 ] Available from: https://doi.org/10.1109/CAIN66642.2025.00041 - An integrated implementation of probabilistic graphical models
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Informações sobre o DOI: 10.1109/CAIN66642.2025.00041 (Fonte: oaDOI API)
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