Predicting execution time of machine learning tasks for scheduling (2013)
- Authors:
- Autor USP: CARVALHO, ANDRÉ CARLOS PONCE DE LEON FERREIRA DE - ICMC
- Unidade: ICMC
- DOI: 10.3233/HIS-130162
- Subjects: INTELIGÊNCIA ARTIFICIAL; APRENDIZADO COMPUTACIONAL
- Language: Inglês
- Imprenta:
- Source:
- Título do periódico: International Journal of Hybrid Intelligent Systems
- ISSN: 1448-5869
- Volume/Número/Paginação/Ano: v. 10, p. 23-32, 2013
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
PRIYA, Rattan et al. Predicting execution time of machine learning tasks for scheduling. International Journal of Hybrid Intelligent Systems, v. 10, p. 23-32, 2013Tradução . . Disponível em: https://doi.org/10.3233/HIS-130162. Acesso em: 18 abr. 2024. -
APA
Priya, R., Souza, B. F. de, Rossi, A. L. D., & Carvalho, A. C. P. de L. F. de. (2013). Predicting execution time of machine learning tasks for scheduling. International Journal of Hybrid Intelligent Systems, 10, 23-32. doi:10.3233/HIS-130162 -
NLM
Priya R, Souza BF de, Rossi ALD, Carvalho ACP de LF de. Predicting execution time of machine learning tasks for scheduling [Internet]. International Journal of Hybrid Intelligent Systems. 2013 ; 10 23-32.[citado 2024 abr. 18 ] Available from: https://doi.org/10.3233/HIS-130162 -
Vancouver
Priya R, Souza BF de, Rossi ALD, Carvalho ACP de LF de. Predicting execution time of machine learning tasks for scheduling [Internet]. International Journal of Hybrid Intelligent Systems. 2013 ; 10 23-32.[citado 2024 abr. 18 ] Available from: https://doi.org/10.3233/HIS-130162 - Reduction strategies for hierarchical multi-label classification in protein function prediction
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Informações sobre o DOI: 10.3233/HIS-130162 (Fonte: oaDOI API)
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