ReP USP - Resultado da busca

Trabalho de evento
Stochastic density ratio estimation and its application to feature selection (2015)
Braga, Igor; Monard, Maria Carolina (Orientador) ; Vapnik, Vladimir (coorient)
Fonte: Proceedings. Nome do evento: International Joint Conference on Artificial Intelligence - IJCAI. Unidade: ICMC
Assuntos: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BRAGA, Igor. Stochastic density ratio estimation and its application to feature selection. 2015, Anais.. Palo Alto: AAAI Press, 2015. Disponível em: http://ijcai.org/papers15/Papers/IJCAI15-620.pdf. Acesso em: 30 nov. 2025.
APA
Braga, I. (2015). Stochastic density ratio estimation and its application to feature selection. In Proceedings. Palo Alto: AAAI Press. Recuperado de http://ijcai.org/papers15/Papers/IJCAI15-620.pdf
NLM
Braga I. Stochastic density ratio estimation and its application to feature selection [Internet]. Proceedings. 2015 ;[citado 2025 nov. 30 ] Available from: http://ijcai.org/papers15/Papers/IJCAI15-620.pdf
Vancouver
Braga I. Stochastic density ratio estimation and its application to feature selection [Internet]. Proceedings. 2015 ;[citado 2025 nov. 30 ] Available from: http://ijcai.org/papers15/Papers/IJCAI15-620.pdf
Artigo de periodico
Lazy multi-label learning algorithms based on mutuality strategies (2015)
Cherman, Everton Alvares; Spolaôr, Newton; Valverde-Rebaza, Jorge; Monard, Maria Carolina
Fonte: Journal of Intelligent and Robotic Systems. Unidade: ICMC
Assuntos: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CHERMAN, Everton Alvares et al. Lazy multi-label learning algorithms based on mutuality strategies. Journal of Intelligent and Robotic Systems, v. 80, p. S261-S276, 2015Tradução . . Disponível em: https://doi.org/10.1007/s10846-014-0144-4. Acesso em: 30 nov. 2025.
APA
Cherman, E. A., Spolaôr, N., Valverde-Rebaza, J., & Monard, M. C. (2015). Lazy multi-label learning algorithms based on mutuality strategies. Journal of Intelligent and Robotic Systems, 80, S261-S276. doi:10.1007/s10846-014-0144-4
NLM
Cherman EA, Spolaôr N, Valverde-Rebaza J, Monard MC. Lazy multi-label learning algorithms based on mutuality strategies [Internet]. Journal of Intelligent and Robotic Systems. 2015 ; 80 S261-S276.[citado 2025 nov. 30 ] Available from: https://doi.org/10.1007/s10846-014-0144-4
Vancouver
Cherman EA, Spolaôr N, Valverde-Rebaza J, Monard MC. Lazy multi-label learning algorithms based on mutuality strategies [Internet]. Journal of Intelligent and Robotic Systems. 2015 ; 80 S261-S276.[citado 2025 nov. 30 ] Available from: https://doi.org/10.1007/s10846-014-0144-4
Trabalho de evento
FCA-Based Rule Generator: a framework for the genetic generation of fuzzy classification systems using formal concept analysis (2015)
Cintra, Marcos E; Monard, Maria Carolina ; Camargo, Heloisa A
Fonte: Proceedings. Nome do evento: IEEE International Conference on Fuzzy Systems - FUZZ-IEEE. Unidade: ICMC
Assuntos: INTELIGÊNCIA ARTIFICIAL, FUZZY (INTELIGÊNCIA ARTIFICIAL)
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CINTRA, Marcos E e MONARD, Maria Carolina e CAMARGO, Heloisa A. FCA-Based Rule Generator: a framework for the genetic generation of fuzzy classification systems using formal concept analysis. 2015, Anais.. Piscataway: IEEE, 2015. Disponível em: https://doi.org/10.1109/FUZZ-IEEE.2015.7337950. Acesso em: 30 nov. 2025.
APA
Cintra, M. E., Monard, M. C., & Camargo, H. A. (2015). FCA-Based Rule Generator: a framework for the genetic generation of fuzzy classification systems using formal concept analysis. In Proceedings. Piscataway: IEEE. doi:10.1109/FUZZ-IEEE.2015.7337950
NLM
Cintra ME, Monard MC, Camargo HA. FCA-Based Rule Generator: a framework for the genetic generation of fuzzy classification systems using formal concept analysis [Internet]. Proceedings. 2015 ;[citado 2025 nov. 30 ] Available from: https://doi.org/10.1109/FUZZ-IEEE.2015.7337950
Vancouver
Cintra ME, Monard MC, Camargo HA. FCA-Based Rule Generator: a framework for the genetic generation of fuzzy classification systems using formal concept analysis [Internet]. Proceedings. 2015 ;[citado 2025 nov. 30 ] Available from: https://doi.org/10.1109/FUZZ-IEEE.2015.7337950
Artigo de periodico
Improving the kernel regularized least squares method for small-sample regression (2015)
Braga, Igor; Monard, Maria Carolina
Fonte: Neurocomputing. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BRAGA, Igor e MONARD, Maria Carolina. Improving the kernel regularized least squares method for small-sample regression. Neurocomputing, v. 163, p. 106-114, 2015Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2014.12.097. Acesso em: 30 nov. 2025.
APA
Braga, I., & Monard, M. C. (2015). Improving the kernel regularized least squares method for small-sample regression. Neurocomputing, 163, 106-114. doi:10.1016/j.neucom.2014.12.097
NLM
Braga I, Monard MC. Improving the kernel regularized least squares method for small-sample regression [Internet]. Neurocomputing. 2015 ; 163 106-114.[citado 2025 nov. 30 ] Available from: https://doi.org/10.1016/j.neucom.2014.12.097
Vancouver
Braga I, Monard MC. Improving the kernel regularized least squares method for small-sample regression [Internet]. Neurocomputing. 2015 ; 163 106-114.[citado 2025 nov. 30 ] Available from: https://doi.org/10.1016/j.neucom.2014.12.097
Trabalho de evento
Feature selection for multi-label learning (2015)
Spolaôr, Newton; Monard, Maria Carolina ; Lee, Huei Diana
Fonte: Proceedings. Nome do evento: International Joint Conference on Artificial Intelligence - IJCAI. Unidade: ICMC
Assuntos: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SPOLAÔR, Newton e MONARD, Maria Carolina e LEE, Huei Diana. Feature selection for multi-label learning. 2015, Anais.. Palo Alto: AAAI Press, 2015. Disponível em: http://ijcai.org/papers15/Papers/IJCAI15-648.pdf. Acesso em: 30 nov. 2025.
APA
Spolaôr, N., Monard, M. C., & Lee, H. D. (2015). Feature selection for multi-label learning. In Proceedings. Palo Alto: AAAI Press. Recuperado de http://ijcai.org/papers15/Papers/IJCAI15-648.pdf
NLM
Spolaôr N, Monard MC, Lee HD. Feature selection for multi-label learning [Internet]. Proceedings. 2015 ;[citado 2025 nov. 30 ] Available from: http://ijcai.org/papers15/Papers/IJCAI15-648.pdf
Vancouver
Spolaôr N, Monard MC, Lee HD. Feature selection for multi-label learning [Internet]. Proceedings. 2015 ;[citado 2025 nov. 30 ] Available from: http://ijcai.org/papers15/Papers/IJCAI15-648.pdf

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