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Trabalho de evento-anais periodico
Exploring text decoding methods for portuguese legal text generation (2023)
Sakiyama, Kenzo ; Montanari, Raphael ; Malaquias Junior, Roseval Donisete ; Nogueira, Rodrigo Frassetto ; Romero, Roseli Aparecida Francelin
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: Brazilian Conference on Intelligent Systems - BRACIS. Unidades: ICMC, EESC
Assuntos: PROCESSAMENTO DE LINGUAGEM NATURAL, TRATAMENTO AUTOMÁTICO DE TEXTOS E DISCURSOS, RECUPERAÇÃO DA INFORMAÇÃO, PORTUGUÊS DO BRASIL
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SAKIYAMA, Kenzo et al. Exploring text decoding methods for portuguese legal text generation. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-45368-7_5. Acesso em: 30 abr. 2024. , 2023
APA
Sakiyama, K., Montanari, R., Malaquias Junior, R. D., Nogueira, R. F., & Romero, R. A. F. (2023). Exploring text decoding methods for portuguese legal text generation. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-031-45368-7_5
NLM
Sakiyama K, Montanari R, Malaquias Junior RD, Nogueira RF, Romero RAF. Exploring text decoding methods for portuguese legal text generation [Internet]. Lecture Notes in Artificial Intelligence. 2023 ; 14195 63-77.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-031-45368-7_5
Vancouver
Sakiyama K, Montanari R, Malaquias Junior RD, Nogueira RF, Romero RAF. Exploring text decoding methods for portuguese legal text generation [Internet]. Lecture Notes in Artificial Intelligence. 2023 ; 14195 63-77.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-031-45368-7_5
Trabalho de evento-anais periodico
Regulation and ethics of facial recognition systems: an analysis of cases in the Court of Appeal in the state of São Paulo (2023)
Oliveira, Cristina Godoy Bernardo de; Albuquerque, Otávio de Paula ; Belotti, Emily Liene; Lopes, Isabella Ferreira; Silva, Rodrigo Brandão de Andrade e; Arbix, Glauco Antonio Truzzi
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: Brazilian Conference on Intelligent Systems - BRACIS. Unidades: FDRP, FFLCH, EESC E ICMC, EACH
Assuntos: RECONHECIMENTO DE IMAGEM, MINERAÇÃO DE DADOS, DIREITO DO CONSUMIDOR, JURISPRUDÊNCIA, CRÉDITO BANCÁRIO
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OLIVEIRA, Cristina Godoy Bernardo de et al. Regulation and ethics of facial recognition systems: an analysis of cases in the Court of Appeal in the state of São Paulo. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-45368-7_2. Acesso em: 30 abr. 2024. , 2023
APA
Oliveira, C. G. B. de, Albuquerque, O. de P., Belotti, E. L., Lopes, I. F., Silva, R. B. de A. e, & Arbix, G. A. T. (2023). Regulation and ethics of facial recognition systems: an analysis of cases in the Court of Appeal in the state of São Paulo. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-031-45368-7_2
NLM
Oliveira CGB de, Albuquerque O de P, Belotti EL, Lopes IF, Silva RB de A e, Arbix GAT. Regulation and ethics of facial recognition systems: an analysis of cases in the Court of Appeal in the state of São Paulo [Internet]. Lecture Notes in Artificial Intelligence. 2023 ; 14195 18-32.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-031-45368-7_2
Vancouver
Oliveira CGB de, Albuquerque O de P, Belotti EL, Lopes IF, Silva RB de A e, Arbix GAT. Regulation and ethics of facial recognition systems: an analysis of cases in the Court of Appeal in the state of São Paulo [Internet]. Lecture Notes in Artificial Intelligence. 2023 ; 14195 18-32.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-031-45368-7_2
Trabalho de evento-anais periodico
Disambiguation of Universal Dependencies part-of-speech tags of closed class words in portuguese (2023)
Lopes, Lucelene ; Fernandes, Paulo ; Inácio, Marcio Lima ; Duran, Magali Sanches ; Pardo, Thiago Alexandre Salgueiro
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Assuntos: PROCESSAMENTO DE LINGUAGEM NATURAL, SINTAXE E SEMÂNTICA DA LINGUAGEM NATURAL, PORTUGUÊS DO BRASIL
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LOPES, Lucelene et al. Disambiguation of Universal Dependencies part-of-speech tags of closed class words in portuguese. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-45392-2_16. Acesso em: 30 abr. 2024. , 2023
APA
Lopes, L., Fernandes, P., Inácio, M. L., Duran, M. S., & Pardo, T. A. S. (2023). Disambiguation of Universal Dependencies part-of-speech tags of closed class words in portuguese. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-031-45392-2_16
NLM
Lopes L, Fernandes P, Inácio ML, Duran MS, Pardo TAS. Disambiguation of Universal Dependencies part-of-speech tags of closed class words in portuguese [Internet]. Lecture Notes in Artificial Intelligence. 2023 ; 14197 241-255.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-031-45392-2_16
Vancouver
Lopes L, Fernandes P, Inácio ML, Duran MS, Pardo TAS. Disambiguation of Universal Dependencies part-of-speech tags of closed class words in portuguese [Internet]. Lecture Notes in Artificial Intelligence. 2023 ; 14197 241-255.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-031-45392-2_16
Trabalho de evento-anais periodico
Analyzing college student dropout risk prediction in real data using walk-forward validation (2023)
Santos, Rodolfo Sanches Saraiva dos ; Ponti, Moacir Antonelli ; Rodrigues, Kamila Rios da Hora
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, ENSINO SUPERIOR, EVASÃO ESCOLAR
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SANTOS, Rodolfo Sanches Saraiva dos e PONTI, Moacir Antonelli e RODRIGUES, Kamila Rios da Hora. Analyzing college student dropout risk prediction in real data using walk-forward validation. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-45368-7_19. Acesso em: 30 abr. 2024. , 2023
APA
Santos, R. S. S. dos, Ponti, M. A., & Rodrigues, K. R. da H. (2023). Analyzing college student dropout risk prediction in real data using walk-forward validation. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-031-45368-7_19
NLM
Santos RSS dos, Ponti MA, Rodrigues KR da H. Analyzing college student dropout risk prediction in real data using walk-forward validation [Internet]. Lecture Notes in Artificial Intelligence. 2023 ; 14195 291-305.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-031-45368-7_19
Vancouver
Santos RSS dos, Ponti MA, Rodrigues KR da H. Analyzing college student dropout risk prediction in real data using walk-forward validation [Internet]. Lecture Notes in Artificial Intelligence. 2023 ; 14195 291-305.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-031-45368-7_19
Trabalho de evento-anais periodico
A framework for controversial political topics identification using Twitter data (2023)
Sakiyama, Kenzo ; Rodrigues, Lucas de Souza ; Nogueira, Bruno Magalhães ; Matsubara, Edson Takashi ; Romero, Roseli Aparecida Francelin
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, PROCESSAMENTO DE LINGUAGEM NATURAL, RECONHECIMENTO DE TEXTO, EMOÇÕES, PORTUGUÊS DO BRASIL, MÍDIAS SOCIAIS
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ABNT
SAKIYAMA, Kenzo et al. A framework for controversial political topics identification using Twitter data. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-45392-2_19. Acesso em: 30 abr. 2024. , 2023
APA
Sakiyama, K., Rodrigues, L. de S., Nogueira, B. M., Matsubara, E. T., & Romero, R. A. F. (2023). A framework for controversial political topics identification using Twitter data. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-031-45392-2_19
NLM
Sakiyama K, Rodrigues L de S, Nogueira BM, Matsubara ET, Romero RAF. A framework for controversial political topics identification using Twitter data [Internet]. Lecture Notes in Artificial Intelligence. 2023 ; 14197 283-298.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-031-45392-2_19
Vancouver
Sakiyama K, Rodrigues L de S, Nogueira BM, Matsubara ET, Romero RAF. A framework for controversial political topics identification using Twitter data [Internet]. Lecture Notes in Artificial Intelligence. 2023 ; 14197 283-298.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-031-45392-2_19
Trabalho de evento-anais periodico
Ulysses-RFSQ: a novel method to improve legal information retrieval based on relevance feedback (2022)
Vitório, Douglas ; Souza, Ellen Polliana Ramos ; Martins, Lucas ; Silva, Nádia Felix Felipe da ; Carvalho, André Carlos Ponce de Leon Ferreira de ; Oliveira, Adriano Lorena Inacio de
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: Brazilian Conference on Intelligent Systems - BRACIS. Unidades: ICMC, EESC E ICMC
Assuntos: RECUPERAÇÃO DA INFORMAÇÃO, RECONHECIMENTO DE TEXTO, PROCESSAMENTO DE LINGUAGEM NATURAL, APRENDIZADO COMPUTACIONAL
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VITÓRIO, Douglas et al. Ulysses-RFSQ: a novel method to improve legal information retrieval based on relevance feedback. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-21686-2_6. Acesso em: 30 abr. 2024. , 2022
APA
Vitório, D., Souza, E. P. R., Martins, L., Silva, N. F. F. da, Carvalho, A. C. P. de L. F. de, & Oliveira, A. L. I. de. (2022). Ulysses-RFSQ: a novel method to improve legal information retrieval based on relevance feedback. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-031-21686-2_6
NLM
Vitório D, Souza EPR, Martins L, Silva NFF da, Carvalho ACP de LF de, Oliveira ALI de. Ulysses-RFSQ: a novel method to improve legal information retrieval based on relevance feedback [Internet]. Lecture Notes in Artificial Intelligence. 2022 ; 13653 77-91.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-031-21686-2_6
Vancouver
Vitório D, Souza EPR, Martins L, Silva NFF da, Carvalho ACP de LF de, Oliveira ALI de. Ulysses-RFSQ: a novel method to improve legal information retrieval based on relevance feedback [Internet]. Lecture Notes in Artificial Intelligence. 2022 ; 13653 77-91.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-031-21686-2_6
Trabalho de evento
Hyperintensional models and belief change (2022)
Souza, Marlo ; Wassermann, Renata
Fonte: Proceedings. Nome do evento: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: IME
Assuntos: REVISÃO DE CRENÇAS, LÓGICA MATEMÁTICA
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SOUZA, Marlo e WASSERMANN, Renata. Hyperintensional models and belief change. 2022, Anais.. Cham: Springer, 2022. Disponível em: https://doi.org/10.1007/978-3-031-21686-2_30. Acesso em: 30 abr. 2024.
APA
Souza, M., & Wassermann, R. (2022). Hyperintensional models and belief change. In Proceedings. Cham: Springer. doi:10.1007/978-3-031-21686-2_30
NLM
Souza M, Wassermann R. Hyperintensional models and belief change [Internet]. Proceedings. 2022 ;[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-031-21686-2_30
Vancouver
Souza M, Wassermann R. Hyperintensional models and belief change [Internet]. Proceedings. 2022 ;[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-031-21686-2_30
Trabalho de evento-anais periodico
A network-based visual analytics approach for performance evaluation of swarms of robots in the surveillance task (2022)
Linhares, Claudio Douglas Gouveia ; Tinoco, Claudiney Ramos ; Ponciano, Jean Roberto ; Oliveira, Gina Maira Barbosa de; Travençolo, Bruno Augusto Nassif
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Assuntos: ROBÓTICA, VISÃO COMPUTACIONAL, VISUALIZAÇÃO, REDES COMPLEXAS
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ABNT
LINHARES, Claudio Douglas Gouveia et al. A network-based visual analytics approach for performance evaluation of swarms of robots in the surveillance task. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-21686-2_5. Acesso em: 30 abr. 2024. , 2022
APA
Linhares, C. D. G., Tinoco, C. R., Ponciano, J. R., Oliveira, G. M. B. de, & Travençolo, B. A. N. (2022). A network-based visual analytics approach for performance evaluation of swarms of robots in the surveillance task. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-031-21686-2_5
NLM
Linhares CDG, Tinoco CR, Ponciano JR, Oliveira GMB de, Travençolo BAN. A network-based visual analytics approach for performance evaluation of swarms of robots in the surveillance task [Internet]. Lecture Notes in Artificial Intelligence. 2022 ; 13653 61-76.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-031-21686-2_5
Vancouver
Linhares CDG, Tinoco CR, Ponciano JR, Oliveira GMB de, Travençolo BAN. A network-based visual analytics approach for performance evaluation of swarms of robots in the surveillance task [Internet]. Lecture Notes in Artificial Intelligence. 2022 ; 13653 61-76.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-031-21686-2_5
Trabalho de evento
Time robust trees: using temporal invariance to improve generalization (2022)
Moneda, Luis ; Mauá, Denis Deratani
Fonte: Proceedings. Nome do evento: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: IME
Assuntos: INVARIANTES, TEORIA DA DECISÃO
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ABNT
MONEDA, Luis e MAUÁ, Denis Deratani. Time robust trees: using temporal invariance to improve generalization. 2022, Anais.. Cham: Springer, 2022. Disponível em: https://doi.org/10.1007/978-3-031-21686-2_27. Acesso em: 30 abr. 2024.
APA
Moneda, L., & Mauá, D. D. (2022). Time robust trees: using temporal invariance to improve generalization. In Proceedings. Cham: Springer. doi:10.1007/978-3-031-21686-2_27
NLM
Moneda L, Mauá DD. Time robust trees: using temporal invariance to improve generalization [Internet]. Proceedings. 2022 ;[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-031-21686-2_27
Vancouver
Moneda L, Mauá DD. Time robust trees: using temporal invariance to improve generalization [Internet]. Proceedings. 2022 ;[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-031-21686-2_27
Trabalho de evento-anais periodico
Geographic context-based stacking learning for election prediction from socio-economic data (2022)
Silva, Tiago Pinho da ; Parmezan, Antonio Rafael Sabino ; Batista, Gustavo Enrique de Almeida Prado Alves
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, COMPORTAMENTO ELEITORAL
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SILVA, Tiago Pinho da e PARMEZAN, Antonio Rafael Sabino e BATISTA, Gustavo Enrique de Almeida Prado Alves. Geographic context-based stacking learning for election prediction from socio-economic data. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-21686-2_44. Acesso em: 30 abr. 2024. , 2022
APA
Silva, T. P. da, Parmezan, A. R. S., & Batista, G. E. de A. P. A. (2022). Geographic context-based stacking learning for election prediction from socio-economic data. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-031-21686-2_44
NLM
Silva TP da, Parmezan ARS, Batista GE de APA. Geographic context-based stacking learning for election prediction from socio-economic data [Internet]. Lecture Notes in Artificial Intelligence. 2022 ; 13653 641-657.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-031-21686-2_44
Vancouver
Silva TP da, Parmezan ARS, Batista GE de APA. Geographic context-based stacking learning for election prediction from socio-economic data [Internet]. Lecture Notes in Artificial Intelligence. 2022 ; 13653 641-657.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-031-21686-2_44
Trabalho de evento
Exploration versus exploitation in model-based reinforcement learning: an empirical study (2022)
Lovatto, Ângelo Gregório ; Barros, Leliane Nunes de ; Mauá, Denis Deratani
Fonte: Proceedings. Nome do evento: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: IME
Assunto: CONTROLE ÓTIMO
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ABNT
LOVATTO, Ângelo Gregório e BARROS, Leliane Nunes de e MAUÁ, Denis Deratani. Exploration versus exploitation in model-based reinforcement learning: an empirical study. 2022, Anais.. Cham: Springer, 2022. Disponível em: https://doi.org/10.1007/978-3-031-21689-3_3. Acesso em: 30 abr. 2024.
APA
Lovatto, Â. G., Barros, L. N. de, & Mauá, D. D. (2022). Exploration versus exploitation in model-based reinforcement learning: an empirical study. In Proceedings. Cham: Springer. doi:10.1007/978-3-031-21689-3_3
NLM
Lovatto ÂG, Barros LN de, Mauá DD. Exploration versus exploitation in model-based reinforcement learning: an empirical study [Internet]. Proceedings. 2022 ;[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-031-21689-3_3
Vancouver
Lovatto ÂG, Barros LN de, Mauá DD. Exploration versus exploitation in model-based reinforcement learning: an empirical study [Internet]. Proceedings. 2022 ;[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-031-21689-3_3
Trabalho de evento-anais periodico
Extreme learning machine to graph convolutional networks (2022)
Gonçalves, Thales ; Rodrigues, Francisco Aparecido
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, REDES COMPLEXAS, ALGORITMOS
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GONÇALVES, Thales e RODRIGUES, Francisco Aparecido. Extreme learning machine to graph convolutional networks. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-21689-3_42. Acesso em: 30 abr. 2024. , 2022
APA
Gonçalves, T., & Rodrigues, F. A. (2022). Extreme learning machine to graph convolutional networks. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-031-21689-3_42
NLM
Gonçalves T, Rodrigues FA. Extreme learning machine to graph convolutional networks [Internet]. Lecture Notes in Artificial Intelligence. 2022 ; 13654 601-615.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-031-21689-3_42
Vancouver
Gonçalves T, Rodrigues FA. Extreme learning machine to graph convolutional networks [Internet]. Lecture Notes in Artificial Intelligence. 2022 ; 13654 601-615.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-031-21689-3_42
Trabalho de evento-anais periodico
Sequential short-text classification from multiple textual representations with weak supervision (2022)
Reis Filho, Ivan José ; Martins, Luiz Henrique Dutra ; Parmezan, Antonio Rafael Sabino ; Marcacini, Ricardo Marcondes ; Rezende, Solange Oliveira
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE TEXTO, MINERAÇÃO DE DADOS, ANÁLISE DE SÉRIES TEMPORAIS
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ABNT
REIS FILHO, Ivan José et al. Sequential short-text classification from multiple textual representations with weak supervision. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-031-21686-2_12. Acesso em: 30 abr. 2024. , 2022
APA
Reis Filho, I. J., Martins, L. H. D., Parmezan, A. R. S., Marcacini, R. M., & Rezende, S. O. (2022). Sequential short-text classification from multiple textual representations with weak supervision. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-031-21686-2_12
NLM
Reis Filho IJ, Martins LHD, Parmezan ARS, Marcacini RM, Rezende SO. Sequential short-text classification from multiple textual representations with weak supervision [Internet]. Lecture Notes in Artificial Intelligence. 2022 ; 13653 165-179.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-031-21686-2_12
Vancouver
Reis Filho IJ, Martins LHD, Parmezan ARS, Marcacini RM, Rezende SO. Sequential short-text classification from multiple textual representations with weak supervision [Internet]. Lecture Notes in Artificial Intelligence. 2022 ; 13653 165-179.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-031-21686-2_12
Trabalho de evento
Gradient estimation in model-based reinforcement learning: a study on linear quadratic environments (2021)
Lovatto, Ângelo Gregório ; Bueno, Thiago Pereira ; Barros, Leliane Nunes de
Fonte: Proceedings. Nome do evento: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: IME
Assuntos: MODELOS PARA PROCESSOS ESTOCÁSTICOS, APRENDIZADO COMPUTACIONAL
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ABNT
LOVATTO, Ângelo Gregório e BUENO, Thiago Pereira e BARROS, Leliane Nunes de. Gradient estimation in model-based reinforcement learning: a study on linear quadratic environments. 2021, Anais.. Cham: Springer, 2021. Disponível em: https://doi.org/10.1007/978-3-030-91702-9_3. Acesso em: 30 abr. 2024.
APA
Lovatto, Â. G., Bueno, T. P., & Barros, L. N. de. (2021). Gradient estimation in model-based reinforcement learning: a study on linear quadratic environments. In Proceedings. Cham: Springer. doi:10.1007/978-3-030-91702-9_3
NLM
Lovatto ÂG, Bueno TP, Barros LN de. Gradient estimation in model-based reinforcement learning: a study on linear quadratic environments [Internet]. Proceedings. 2021 ;[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-030-91702-9_3
Vancouver
Lovatto ÂG, Bueno TP, Barros LN de. Gradient estimation in model-based reinforcement learning: a study on linear quadratic environments [Internet]. Proceedings. 2021 ;[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-030-91702-9_3
Trabalho de evento-anais periodico
Evaluating clustering meta-features for classifier recommendation (2021)
Garcia, Luís Paulo Faina ; Campelo, Felipe ; Ramos, Guilherme N ; Rivolli, Adriano ; Carvalho, André Carlos Ponce de Leon Ferreira de
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, DESCOBERTA DE CONHECIMENTO, RECONHECIMENTO DE PADRÕES
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ABNT
GARCIA, Luís Paulo Faina et al. Evaluating clustering meta-features for classifier recommendation. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-91702-9_30. Acesso em: 30 abr. 2024. , 2021
APA
Garcia, L. P. F., Campelo, F., Ramos, G. N., Rivolli, A., & Carvalho, A. C. P. de L. F. de. (2021). Evaluating clustering meta-features for classifier recommendation. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-030-91702-9_30
NLM
Garcia LPF, Campelo F, Ramos GN, Rivolli A, Carvalho ACP de LF de. Evaluating clustering meta-features for classifier recommendation [Internet]. Lecture Notes in Artificial Intelligence. 2021 ; 13073 453-467.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-030-91702-9_30
Vancouver
Garcia LPF, Campelo F, Ramos GN, Rivolli A, Carvalho ACP de LF de. Evaluating clustering meta-features for classifier recommendation [Internet]. Lecture Notes in Artificial Intelligence. 2021 ; 13073 453-467.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-030-91702-9_30
Artigo de periodico
Detecting early signs of insufficiency in COVID-19 patients from CBC tests through a supervised learning approach (2021)
Colliri, Tiago; Minakawa, Marcia Michie; Liang, Zhao
Fonte: Lecture Notes in Computer Science. Nome do evento: Brazilian Conference on Intelligent Systems - BRACIS. Unidades: FFCLRP, FSP
Assuntos: REDES COMPLEXAS, COVID-19, PROGNÓSTICO, BIOMARCADORES, CONTAGEM DE CÉLULAS SANGUÍNEAS, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
COLLIRI, Tiago e MINAKAWA, Marcia Michie e LIANG, Zhao. Detecting early signs of insufficiency in COVID-19 patients from CBC tests through a supervised learning approach. Lecture Notes in Computer Science, v. 13074, p. 42-57, 2021Tradução . . Disponível em: https://doi.org/10.1007/978-3-030-91699-2_4. Acesso em: 30 abr. 2024.
APA
Colliri, T., Minakawa, M. M., & Liang, Z. (2021). Detecting early signs of insufficiency in COVID-19 patients from CBC tests through a supervised learning approach. Lecture Notes in Computer Science, 13074, 42-57. doi:10.1007/978-3-030-91699-2_4
NLM
Colliri T, Minakawa MM, Liang Z. Detecting early signs of insufficiency in COVID-19 patients from CBC tests through a supervised learning approach [Internet]. Lecture Notes in Computer Science. 2021 ; 13074 42-57.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-030-91699-2_4
Vancouver
Colliri T, Minakawa MM, Liang Z. Detecting early signs of insufficiency in COVID-19 patients from CBC tests through a supervised learning approach [Internet]. Lecture Notes in Computer Science. 2021 ; 13074 42-57.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-030-91699-2_4
Trabalho de evento-anais periodico
A graph-based crossover and soft-repair operators for the steiner tree problem (2021)
Godoi, Giliard Almeida de; Tinós, Renato ; Sanches, Danilo Sipoli
Fonte: Lecture Notes in Computer Science. Nome do evento: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: FFCLRP
Assuntos: TEORIA DOS GRAFOS, OTIMIZAÇÃO COMBINATÓRIA, ALGORITMOS GENÉTICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GODOI, Giliard Almeida de e TINÓS, Renato e SANCHES, Danilo Sipoli. A graph-based crossover and soft-repair operators for the steiner tree problem. Lecture Notes in Computer Science. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-91702-9_8. Acesso em: 30 abr. 2024. , 2021
APA
Godoi, G. A. de, Tinós, R., & Sanches, D. S. (2021). A graph-based crossover and soft-repair operators for the steiner tree problem. Lecture Notes in Computer Science. Cham: Springer. doi:10.1007/978-3-030-91702-9_8
NLM
Godoi GA de, Tinós R, Sanches DS. A graph-based crossover and soft-repair operators for the steiner tree problem [Internet]. Lecture Notes in Computer Science. 2021 ; 13073 111-125.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-030-91702-9_8
Vancouver
Godoi GA de, Tinós R, Sanches DS. A graph-based crossover and soft-repair operators for the steiner tree problem [Internet]. Lecture Notes in Computer Science. 2021 ; 13073 111-125.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-030-91702-9_8
Trabalho de evento-anais periodico
Universal dependencies-based PoS tagging refinement through linguistic resources (2021)
Lopes, Lucelene ; Duran, Magali Sanches ; Pardo, Thiago Alexandre Salgueiro
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Assuntos: PROCESSAMENTO DE LINGUAGEM NATURAL, LINGUÍSTICA COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
LOPES, Lucelene e DURAN, Magali Sanches e PARDO, Thiago Alexandre Salgueiro. Universal dependencies-based PoS tagging refinement through linguistic resources. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-91699-2_41. Acesso em: 30 abr. 2024. , 2021
APA
Lopes, L., Duran, M. S., & Pardo, T. A. S. (2021). Universal dependencies-based PoS tagging refinement through linguistic resources. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-030-91699-2_41
NLM
Lopes L, Duran MS, Pardo TAS. Universal dependencies-based PoS tagging refinement through linguistic resources [Internet]. Lecture Notes in Artificial Intelligence. 2021 ; 13074 601–615.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-030-91699-2_41
Vancouver
Lopes L, Duran MS, Pardo TAS. Universal dependencies-based PoS tagging refinement through linguistic resources [Internet]. Lecture Notes in Artificial Intelligence. 2021 ; 13074 601–615.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-030-91699-2_41
Artigo de periodico
Coarsening algorithm via semi-synchronous label propagation for bipartite networks (2021)
Valejo, Alan Demétrius Baria; Althoff, Paulo Eduardo; Faleiros, Thiago de Paulo; Chuerubim, Maria Lígia; Yan, Jianglong; Liu, Weiguang; Liang, Zhao
Fonte: Lecture Notes in Computer Science. Nome do evento: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: FFCLRP
Assuntos: REDES COMPLEXAS, ANÁLISE MULTINÍVEL, ESTATÍSTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
VALEJO, Alan Demétrius Baria et al. Coarsening algorithm via semi-synchronous label propagation for bipartite networks. Lecture Notes in Computer Science, v. 13073, p. 437-452, 2021Tradução . . Disponível em: https://doi.org/10.1007/978-3-030-91702-9_29. Acesso em: 30 abr. 2024.
APA
Valejo, A. D. B., Althoff, P. E., Faleiros, T. de P., Chuerubim, M. L., Yan, J., Liu, W., & Liang, Z. (2021). Coarsening algorithm via semi-synchronous label propagation for bipartite networks. Lecture Notes in Computer Science, 13073, 437-452. doi:10.1007/978-3-030-91702-9_29
NLM
Valejo ADB, Althoff PE, Faleiros T de P, Chuerubim ML, Yan J, Liu W, Liang Z. Coarsening algorithm via semi-synchronous label propagation for bipartite networks [Internet]. Lecture Notes in Computer Science. 2021 ; 13073 437-452.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-030-91702-9_29
Vancouver
Valejo ADB, Althoff PE, Faleiros T de P, Chuerubim ML, Yan J, Liu W, Liang Z. Coarsening algorithm via semi-synchronous label propagation for bipartite networks [Internet]. Lecture Notes in Computer Science. 2021 ; 13073 437-452.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-030-91702-9_29
Trabalho de evento-anais periodico
Speech2Phone: a novel and efficient method for training speaker recognition models (2021)
Casanova, Edresson ; Candido Junior, Arnaldo ; Shulby, Christopher Dane ; Oliveira, Frederico Santos de ; Gris, Lucas Rafael Stefanel ; Silva, Hamilton Pereira da ; Aluísio, Sandra Maria ; Ponti, Moacir Antonelli
Fonte: Lecture Notes in Artificial Intelligence. Nome do evento: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Assuntos: PROCESSAMENTO DE LINGUAGEM NATURAL, RECONHECIMENTO DE VOZ, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CASANOVA, Edresson et al. Speech2Phone: a novel and efficient method for training speaker recognition models. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-91699-2_39. Acesso em: 30 abr. 2024. , 2021
APA
Casanova, E., Candido Junior, A., Shulby, C. D., Oliveira, F. S. de, Gris, L. R. S., Silva, H. P. da, et al. (2021). Speech2Phone: a novel and efficient method for training speaker recognition models. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-030-91699-2_39
NLM
Casanova E, Candido Junior A, Shulby CD, Oliveira FS de, Gris LRS, Silva HP da, Aluísio SM, Ponti MA. Speech2Phone: a novel and efficient method for training speaker recognition models [Internet]. Lecture Notes in Artificial Intelligence. 2021 ; 13074 572-585.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-030-91699-2_39
Vancouver
Casanova E, Candido Junior A, Shulby CD, Oliveira FS de, Gris LRS, Silva HP da, Aluísio SM, Ponti MA. Speech2Phone: a novel and efficient method for training speaker recognition models [Internet]. Lecture Notes in Artificial Intelligence. 2021 ; 13074 572-585.[citado 2024 abr. 30 ] Available from: https://doi.org/10.1007/978-3-030-91699-2_39

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