ReP USP - Resultado da busca

Artigo de periodico
Multi-label active learning: key issues and a novel query strategy (2019)
Cherman, Everton Alvares; Papanikolaou, Yannis; Tsoumakas, Grigorios; Monard, Maria Carolina
Source: Evolving Systems. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, DESCOBERTA DE CONHECIMENTO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CHERMAN, Everton Alvares et al. Multi-label active learning: key issues and a novel query strategy. Evolving Systems, v. 10, n. 1, p. 63-78, 2019Tradução . . Disponível em: https://doi.org/10.1007/s12530-017-9202-z. Acesso em: 27 nov. 2025.
APA
Cherman, E. A., Papanikolaou, Y., Tsoumakas, G., & Monard, M. C. (2019). Multi-label active learning: key issues and a novel query strategy. Evolving Systems, 10( 1), 63-78. doi:10.1007/s12530-017-9202-z
NLM
Cherman EA, Papanikolaou Y, Tsoumakas G, Monard MC. Multi-label active learning: key issues and a novel query strategy [Internet]. Evolving Systems. 2019 ; 10( 1): 63-78.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1007/s12530-017-9202-z
Vancouver
Cherman EA, Papanikolaou Y, Tsoumakas G, Monard MC. Multi-label active learning: key issues and a novel query strategy [Internet]. Evolving Systems. 2019 ; 10( 1): 63-78.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1007/s12530-017-9202-z
Artigo de periodico
Genetic generation of fuzzy systems with rule extraction using formal concept analysis (2016)
Cintra, M. E; Camargo, H. A; Monard, Maria Carolina
Source: Information Sciences. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, FUZZY (INTELIGÊNCIA ARTIFICIAL)
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CINTRA, M. E e CAMARGO, H. A e MONARD, Maria Carolina. Genetic generation of fuzzy systems with rule extraction using formal concept analysis. Information Sciences, v. 349-350, p. 199-215, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.ins.2016.02.026. Acesso em: 27 nov. 2025.
APA
Cintra, M. E., Camargo, H. A., & Monard, M. C. (2016). Genetic generation of fuzzy systems with rule extraction using formal concept analysis. Information Sciences, 349-350, 199-215. doi:10.1016/j.ins.2016.02.026
NLM
Cintra ME, Camargo HA, Monard MC. Genetic generation of fuzzy systems with rule extraction using formal concept analysis [Internet]. Information Sciences. 2016 ; 349-350 199-215.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1016/j.ins.2016.02.026
Vancouver
Cintra ME, Camargo HA, Monard MC. Genetic generation of fuzzy systems with rule extraction using formal concept analysis [Internet]. Information Sciences. 2016 ; 349-350 199-215.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1016/j.ins.2016.02.026
Trabalho de evento-anais periodico
Active learning algorithms for multi-label data (2016)
Cherman, Everton Alvares; Tsoumakas, Grigorios; Monard, Maria Carolina
Source: IFIP Advances in Information and Communication Technology. Conference titles: IFIP International Conference and Workshops on Artificial Intelligence Applications and Innovation - AIAI. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CHERMAN, Everton Alvares e TSOUMAKAS, Grigorios e MONARD, Maria Carolina. Active learning algorithms for multi-label data. IFIP Advances in Information and Communication Technology. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-319-44944-9_23. Acesso em: 27 nov. 2025. , 2016
APA
Cherman, E. A., Tsoumakas, G., & Monard, M. C. (2016). Active learning algorithms for multi-label data. IFIP Advances in Information and Communication Technology. Cham: Springer. doi:10.1007/978-3-319-44944-9_23
NLM
Cherman EA, Tsoumakas G, Monard MC. Active learning algorithms for multi-label data [Internet]. IFIP Advances in Information and Communication Technology. 2016 ; 475 267-279.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1007/978-3-319-44944-9_23
Vancouver
Cherman EA, Tsoumakas G, Monard MC. Active learning algorithms for multi-label data [Internet]. IFIP Advances in Information and Communication Technology. 2016 ; 475 267-279.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1007/978-3-319-44944-9_23
Artigo de periodico
A systematic review of multi-label feature selection and a new method based on label construction (2016)
Spolaôr, Newton; Monard, Maria Carolina ; Tsoumakas, Grigorios; Lee, Huei Diana
Source: Neurocomputing. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SPOLAÔR, Newton et al. A systematic review of multi-label feature selection and a new method based on label construction. Neurocomputing, v. 180, p. 3-15, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2015.07.118. Acesso em: 27 nov. 2025.
APA
Spolaôr, N., Monard, M. C., Tsoumakas, G., & Lee, H. D. (2016). A systematic review of multi-label feature selection and a new method based on label construction. Neurocomputing, 180, 3-15. doi:10.1016/j.neucom.2015.07.118
NLM
Spolaôr N, Monard MC, Tsoumakas G, Lee HD. A systematic review of multi-label feature selection and a new method based on label construction [Internet]. Neurocomputing. 2016 ; 180 3-15.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1016/j.neucom.2015.07.118
Vancouver
Spolaôr N, Monard MC, Tsoumakas G, Lee HD. A systematic review of multi-label feature selection and a new method based on label construction [Internet]. Neurocomputing. 2016 ; 180 3-15.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1016/j.neucom.2015.07.118
Trabalho de evento
Stochastic density ratio estimation and its application to feature selection (2015)
Braga, Igor; Monard, Maria Carolina (Orientador) ; Vapnik, Vladimir (coorient)
Source: Proceedings. Conference titles: International Joint Conference on Artificial Intelligence - IJCAI. Unidade: ICMC
Subjects: 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: 27 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. 27 ] 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. 27 ] 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
Source: Journal of Intelligent and Robotic Systems. Unidade: ICMC
Subjects: 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: 27 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. 27 ] 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. 27 ] 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
Source: Proceedings. Conference titles: IEEE International Conference on Fuzzy Systems - FUZZ-IEEE. Unidade: ICMC
Subjects: 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: 27 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. 27 ] 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. 27 ] 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
Source: 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: 27 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. 27 ] 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. 27 ] 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
Source: Proceedings. Conference titles: International Joint Conference on Artificial Intelligence - IJCAI. Unidade: ICMC
Subjects: 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: 27 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. 27 ] 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. 27 ] Available from: http://ijcai.org/papers15/Papers/IJCAI15-648.pdf
Trabalho de evento
Label construction for multi-label feature selection (2014)
Spolaôr, Newton; Monard, Maria Carolina ; Tsoumakas, Grigorios; Lee, Huei Diana
Source: Proceedings. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SPOLAÔR, Newton et al. Label construction for multi-label feature selection. 2014, Anais.. Los Alamitos: Conference Publishing Services, 2014. Disponível em: https://doi.org/10.1109/BRACIS.2014.52. Acesso em: 27 nov. 2025.
APA
Spolaôr, N., Monard, M. C., Tsoumakas, G., & Lee, H. D. (2014). Label construction for multi-label feature selection. In Proceedings. Los Alamitos: Conference Publishing Services. doi:10.1109/BRACIS.2014.52
NLM
Spolaôr N, Monard MC, Tsoumakas G, Lee HD. Label construction for multi-label feature selection [Internet]. Proceedings. 2014 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/BRACIS.2014.52
Vancouver
Spolaôr N, Monard MC, Tsoumakas G, Lee HD. Label construction for multi-label feature selection [Internet]. Proceedings. 2014 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/BRACIS.2014.52
Trabalho de evento-anais periodico
A framework to generate synthetic multi-label datasets (2014)
Tomás, Jimena Torres; Spolaôr, Newton; Cherman, Everton Alvares; Monard, Maria Carolina
Source: Electronic Notes in Theoretical Computer Science. Conference titles: Latin American Computing Conference - CLEI. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
TOMÁS, Jimena Torres et al. A framework to generate synthetic multi-label datasets. Electronic Notes in Theoretical Computer Science. Amsterdam: Elsevier. Disponível em: https://doi.org/10.1016/j.entcs.2014.01.025. Acesso em: 27 nov. 2025. , 2014
APA
Tomás, J. T., Spolaôr, N., Cherman, E. A., & Monard, M. C. (2014). A framework to generate synthetic multi-label datasets. Electronic Notes in Theoretical Computer Science. Amsterdam: Elsevier. doi:10.1016/j.entcs.2014.01.025
NLM
Tomás JT, Spolaôr N, Cherman EA, Monard MC. A framework to generate synthetic multi-label datasets [Internet]. Electronic Notes in Theoretical Computer Science. 2014 ; fe 2014 155-176.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1016/j.entcs.2014.01.025
Vancouver
Tomás JT, Spolaôr N, Cherman EA, Monard MC. A framework to generate synthetic multi-label datasets [Internet]. Electronic Notes in Theoretical Computer Science. 2014 ; fe 2014 155-176.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1016/j.entcs.2014.01.025
Trabalho de evento-anais periodico
Evaluating ReliefF-based multi-label feature selection algorithm (2014)
Spolaôr, Newton; Monard, Maria Carolina
Source: Lecture Notes in Artifical Intelligence. Conference titles: Ibero-American Conference on Artificial Intelligence - IBERAMIA : Advances in Artificial Intelligence. Unidade: ICMC
Subjects: 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. Evaluating ReliefF-based multi-label feature selection algorithm. Lecture Notes in Artifical Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-319-12027-0_16. Acesso em: 27 nov. 2025. , 2014
APA
Spolaôr, N., & Monard, M. C. (2014). Evaluating ReliefF-based multi-label feature selection algorithm. Lecture Notes in Artifical Intelligence. Cham: Springer. doi:10.1007/978-3-319-12027-0_16
NLM
Spolaôr N, Monard MC. Evaluating ReliefF-based multi-label feature selection algorithm [Internet]. Lecture Notes in Artifical Intelligence. 2014 ; 8864 194-205.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1007/978-3-319-12027-0_16
Vancouver
Spolaôr N, Monard MC. Evaluating ReliefF-based multi-label feature selection algorithm [Internet]. Lecture Notes in Artifical Intelligence. 2014 ; 8864 194-205.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1007/978-3-319-12027-0_16
Trabalho de evento
A framework for multi-label exploratory data analysis: ML-EDA (2014)
Carvalho, Victor Augusto Moraes; Spolaôr, Newton; Cherman, Everton Alvares; Monard, Maria Carolina
Source: Proceedings. Conference titles: Latin American Computing Conference - CLEI. Unidade: ICMC
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL, COMPUTAÇÃO GRÁFICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CARVALHO, Victor Augusto Moraes et al. A framework for multi-label exploratory data analysis: ML-EDA. 2014, Anais.. Red Hook: IEEE, 2014. Disponível em: https://doi.org/10.1109/CLEI.2014.6965166. Acesso em: 27 nov. 2025.
APA
Carvalho, V. A. M., Spolaôr, N., Cherman, E. A., & Monard, M. C. (2014). A framework for multi-label exploratory data analysis: ML-EDA. In Proceedings. Red Hook: IEEE. doi:10.1109/CLEI.2014.6965166
NLM
Carvalho VAM, Spolaôr N, Cherman EA, Monard MC. A framework for multi-label exploratory data analysis: ML-EDA [Internet]. Proceedings. 2014 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/CLEI.2014.6965166
Vancouver
Carvalho VAM, Spolaôr N, Cherman EA, Monard MC. A framework for multi-label exploratory data analysis: ML-EDA [Internet]. Proceedings. 2014 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/CLEI.2014.6965166
Trabalho de evento
ReliefF for multi-label feature selection (2013)
Spolaôr, Newton; Cherman, Everton Alvares; Monard, Maria Carolina ; Lee, Huei Diana
Source: Proceedings. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SPOLAÔR, Newton et al. ReliefF for multi-label feature selection. 2013, Anais.. Los Alamitos: Conference Publishing Services, 2013. Disponível em: https://doi.org/10.1109/BRACIS.2013.10. Acesso em: 27 nov. 2025.
APA
Spolaôr, N., Cherman, E. A., Monard, M. C., & Lee, H. D. (2013). ReliefF for multi-label feature selection. In Proceedings. Los Alamitos: Conference Publishing Services. doi:10.1109/BRACIS.2013.10
NLM
Spolaôr N, Cherman EA, Monard MC, Lee HD. ReliefF for multi-label feature selection [Internet]. Proceedings. 2013 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/BRACIS.2013.10
Vancouver
Spolaôr N, Cherman EA, Monard MC, Lee HD. ReliefF for multi-label feature selection [Internet]. Proceedings. 2013 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/BRACIS.2013.10
Trabalho de evento-anais periodico
A note on parameter selection for support vector machines (2013)
Braga, Igor; Carmo, Laís P. do; Benatti, Caio César; Monard, Maria Carolina
Source: Lecture Notes in Artificial Intelligence. Conference titles: Mexican International Conference on Artificial Intelligence : Advances in Soft Computing and its Applications - MICAI. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BRAGA, Igor et al. A note on parameter selection for support vector machines. Lecture Notes in Artificial Intelligence. Berlin: Springer-Verlag. Disponível em: https://doi.org/10.1007/978-3-642-45111-9_21. Acesso em: 27 nov. 2025. , 2013
APA
Braga, I., Carmo, L. P. do, Benatti, C. C., & Monard, M. C. (2013). A note on parameter selection for support vector machines. Lecture Notes in Artificial Intelligence. Berlin: Springer-Verlag. doi:10.1007/978-3-642-45111-9_21
NLM
Braga I, Carmo LP do, Benatti CC, Monard MC. A note on parameter selection for support vector machines [Internet]. Lecture Notes in Artificial Intelligence. 2013 ; 8266 233-244.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1007/978-3-642-45111-9_21
Vancouver
Braga I, Carmo LP do, Benatti CC, Monard MC. A note on parameter selection for support vector machines [Internet]. Lecture Notes in Artificial Intelligence. 2013 ; 8266 233-244.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1007/978-3-642-45111-9_21
Trabalho de evento
Statistical and heuristic model selection in regularized least-squares (2013)
Braga, Igor; Monard, Maria Carolina
Source: Proceedings. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. 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. Statistical and heuristic model selection in regularized least-squares. 2013, Anais.. Los Alamitos: Conference Publishing Services, 2013. Disponível em: https://doi.org/10.1109/BRACIS.2013.46. Acesso em: 27 nov. 2025.
APA
Braga, I., & Monard, M. C. (2013). Statistical and heuristic model selection in regularized least-squares. In Proceedings. Los Alamitos: Conference Publishing Services. doi:10.1109/BRACIS.2013.46
NLM
Braga I, Monard MC. Statistical and heuristic model selection in regularized least-squares [Internet]. Proceedings. 2013 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/BRACIS.2013.46
Vancouver
Braga I, Monard MC. Statistical and heuristic model selection in regularized least-squares [Internet]. Proceedings. 2013 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/BRACIS.2013.46
Parte de monografia/livro
On rule learning methods: a comparative analysis of classic and fuzzy approaches (2013)
Cintra, Marcos E; Monard, Maria Carolina ; Camargo, Heloisa A
Unidade: ICMC
Assunto: 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. On rule learning methods: a comparative analysis of classic and fuzzy approaches. Tradução . Berlin: Springer-Verlag, 2013. . . Acesso em: 27 nov. 2025.
APA
Cintra, M. E., Monard, M. C., & Camargo, H. A. (2013). On rule learning methods: a comparative analysis of classic and fuzzy approaches. In . Berlin: Springer-Verlag.
NLM
Cintra ME, Monard MC, Camargo HA. On rule learning methods: a comparative analysis of classic and fuzzy approaches. Berlin: Springer-Verlag; 2013. [citado 2025 nov. 27 ]
Vancouver
Cintra ME, Monard MC, Camargo HA. On rule learning methods: a comparative analysis of classic and fuzzy approaches. Berlin: Springer-Verlag; 2013. [citado 2025 nov. 27 ]
Relatorio tecnico
Projeto e implementação de um framework para a geração de conjunto de dados sintéticos para aprendizado multirrótulo (2013)
Tomás, Jimena Torres; Spolaôr, Newton; Cherman, Everton Alvares; Monard, Maria Carolina
Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
TOMÁS, Jimena Torres et al. Projeto e implementação de um framework para a geração de conjunto de dados sintéticos para aprendizado multirrótulo. . São Carlos: ICMC-USP. Disponível em: http://www2.icmc.usp.br/~biblio/BIBLIOTECA/rel_tec/RT_391.pdf. Acesso em: 27 nov. 2025. , 2013
APA
Tomás, J. T., Spolaôr, N., Cherman, E. A., & Monard, M. C. (2013). Projeto e implementação de um framework para a geração de conjunto de dados sintéticos para aprendizado multirrótulo. São Carlos: ICMC-USP. Recuperado de http://www2.icmc.usp.br/~biblio/BIBLIOTECA/rel_tec/RT_391.pdf
NLM
Tomás JT, Spolaôr N, Cherman EA, Monard MC. Projeto e implementação de um framework para a geração de conjunto de dados sintéticos para aprendizado multirrótulo [Internet]. 2013 ;[citado 2025 nov. 27 ] Available from: http://www2.icmc.usp.br/~biblio/BIBLIOTECA/rel_tec/RT_391.pdf
Vancouver
Tomás JT, Spolaôr N, Cherman EA, Monard MC. Projeto e implementação de um framework para a geração de conjunto de dados sintéticos para aprendizado multirrótulo [Internet]. 2013 ;[citado 2025 nov. 27 ] Available from: http://www2.icmc.usp.br/~biblio/BIBLIOTECA/rel_tec/RT_391.pdf
Trabalho de evento
Uma visão da participação feminina nos cursos de ciência de computação no Brasil (2013)
Monard, Maria Carolina ; Fortes, Renata Pontin de Mattos
Source: Proceedings. Conference titles: Conferencia Latinoamericana en Informática - CLEI. Unidade: ICMC
Assunto: CIÊNCIA DA COMPUTAÇÃO (EDUCAÇÃO)
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MONARD, Maria Carolina e FORTES, Renata Pontin de Mattos. Uma visão da participação feminina nos cursos de ciência de computação no Brasil. 2013, Anais.. Naiguatá: USB, 2013. . Acesso em: 27 nov. 2025.
APA
Monard, M. C., & Fortes, R. P. de M. (2013). Uma visão da participação feminina nos cursos de ciência de computação no Brasil. In Proceedings. Naiguatá: USB.
NLM
Monard MC, Fortes RP de M. Uma visão da participação feminina nos cursos de ciência de computação no Brasil. Proceedings. 2013 ;[citado 2025 nov. 27 ]
Vancouver
Monard MC, Fortes RP de M. Uma visão da participação feminina nos cursos de ciência de computação no Brasil. Proceedings. 2013 ;[citado 2025 nov. 27 ]
Trabalho de evento-anais periodico
A comparison of multi-label feature selection methods using the problem transformation approach (2013)
Spolaôr, Newton; Cherman, Everton Alvares; Monard, Maria Carolina ; Lee, Huei Diana
Source: Electronic Notes in Theoretical Computer Science. Conference titles: Latin American Conference in Informatics - CLEI. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SPOLAÔR, Newton et al. A comparison of multi-label feature selection methods using the problem transformation approach. Electronic Notes in Theoretical Computer Science. Amsterdam: Elsevier. Disponível em: https://doi.org/10.1016/j.entcs.2013.02.010. Acesso em: 27 nov. 2025. , 2013
APA
Spolaôr, N., Cherman, E. A., Monard, M. C., & Lee, H. D. (2013). A comparison of multi-label feature selection methods using the problem transformation approach. Electronic Notes in Theoretical Computer Science. Amsterdam: Elsevier. doi:10.1016/j.entcs.2013.02.010
NLM
Spolaôr N, Cherman EA, Monard MC, Lee HD. A comparison of multi-label feature selection methods using the problem transformation approach [Internet]. Electronic Notes in Theoretical Computer Science. 2013 ; 292( 5): 135-151.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1016/j.entcs.2013.02.010
Vancouver
Spolaôr N, Cherman EA, Monard MC, Lee HD. A comparison of multi-label feature selection methods using the problem transformation approach [Internet]. Electronic Notes in Theoretical Computer Science. 2013 ; 292( 5): 135-151.[citado 2025 nov. 27 ] Available from: https://doi.org/10.1016/j.entcs.2013.02.010

USP Schools

ReP

Filtros

Document Types

USP Schools

Departament

Authors

USP affiliated authors

Date published

Subjects

Source title

Publisher

Conference titles

Countries/Territories

Indexado em

Normalized affiliation

Non normalized affiliation