An optimization framework for combining ensembles of classifiers and clusterers with applications to nontransductive semisupervised learning and transfer learning (2014)
- Authors:
- Autor USP: HRUSCHKA, EDUARDO RAUL - ICMC
- Unidade: ICMC
- DOI: 10.1145/2601435
- Subjects: INTELIGÊNCIA ARTIFICIAL; RECONHECIMENTO DE PADRÕES; ALGORITMOS; VISÃO COMPUTACIONAL
- Language: Inglês
- Imprenta:
- Source:
- Título: ACM Transactions on Knowledge Discovery from Data
- ISSN: 1556-4681
- Volume/Número/Paginação/Ano: v. 9, n. 1, p. 1:1-1:35, ago. 2014
- Este artigo possui versão em acesso aberto
- URL de acesso aberto
- Versão do Documento: Versão submetida (Pré-print)
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Status: Artigo possui versão em acesso aberto em repositório (Green Open Access) -
ABNT
ACHARYA, Ayan et al. An optimization framework for combining ensembles of classifiers and clusterers with applications to nontransductive semisupervised learning and transfer learning. ACM Transactions on Knowledge Discovery from Data, v. 9, n. 1, p. 1:1-1:35, 2014Tradução . . Disponível em: https://doi.org/10.1145/2601435. Acesso em: 13 mar. 2026. -
APA
Acharya, A., Hruschka, E. R., Ghosh, J., & Acharyya, S. (2014). An optimization framework for combining ensembles of classifiers and clusterers with applications to nontransductive semisupervised learning and transfer learning. ACM Transactions on Knowledge Discovery from Data, 9( 1), 1:1-1:35. doi:10.1145/2601435 -
NLM
Acharya A, Hruschka ER, Ghosh J, Acharyya S. An optimization framework for combining ensembles of classifiers and clusterers with applications to nontransductive semisupervised learning and transfer learning [Internet]. ACM Transactions on Knowledge Discovery from Data. 2014 ; 9( 1): 1:1-1:35.[citado 2026 mar. 13 ] Available from: https://doi.org/10.1145/2601435 -
Vancouver
Acharya A, Hruschka ER, Ghosh J, Acharyya S. An optimization framework for combining ensembles of classifiers and clusterers with applications to nontransductive semisupervised learning and transfer learning [Internet]. ACM Transactions on Knowledge Discovery from Data. 2014 ; 9( 1): 1:1-1:35.[citado 2026 mar. 13 ] Available from: https://doi.org/10.1145/2601435 - On the influence of imputation in classification: practical issues
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