Nature-inspired graph optimization for dimensionality reduction (2017)
- Authors:
- Autor USP: LIANG, ZHAO - FFCLRP
- Unidade: FFCLRP
- Subjects: APRENDIZADO COMPUTACIONAL; INTELIGÊNCIA ARTIFICIAL
- Keywords: Graph-based dimensionality reduction; Nature-inspired graph optimization; Graph-based machine learning
- Language: Inglês
- Imprenta:
- Source:
- Título do periódico: Proceedings
- Conference titles: International Conference on Tools with Artficial Intelligence
-
ABNT
CARNEIRO, Murillo G. et al. Nature-inspired graph optimization for dimensionality reduction. 2017, Anais.. Boston: IEEE, 2017. . Acesso em: 30 abr. 2024. -
APA
Carneiro, M. G., Cupertino, T. H., Cheng, R., Jin, Y., & Liang, Z. (2017). Nature-inspired graph optimization for dimensionality reduction. In Proceedings. Boston: IEEE. -
NLM
Carneiro MG, Cupertino TH, Cheng R, Jin Y, Liang Z. Nature-inspired graph optimization for dimensionality reduction. Proceedings. 2017 ;[citado 2024 abr. 30 ] -
Vancouver
Carneiro MG, Cupertino TH, Cheng R, Jin Y, Liang Z. Nature-inspired graph optimization for dimensionality reduction. Proceedings. 2017 ;[citado 2024 abr. 30 ] - Redes de elementos complexos para processamento de informação
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