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Trabalho de evento
Cautious classification with data missing not at random using generative random forests (2021)
Villanueva Llerena, Julissa Giuliana ; Mauá, Denis Deratani ; Antonucci, Alessandro
Source: Proceedings. Conference titles: European Conference on Symbolic and Quantitative Approaches with Uncertainty - ECSQARU. Unidade: IME
Subjects: APRENDIZADO COMPUTACIONAL, MODELOS PARA PROCESSOS ESTOCÁSTICOS
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ABNT
VILLANUEVA LLERENA, Julissa Giuliana e MAUÁ, Denis Deratani e ANTONUCCI, Alessandro. Cautious classification with data missing not at random using generative random forests. 2021, Anais.. Cham: Springer, 2021. Disponível em: https://doi.org/10.1007/978-3-030-86772-0_21. Acesso em: 31 out. 2024.
APA
Villanueva Llerena, J. G., Mauá, D. D., & Antonucci, A. (2021). Cautious classification with data missing not at random using generative random forests. In Proceedings. Cham: Springer. doi:10.1007/978-3-030-86772-0_21
NLM
Villanueva Llerena JG, Mauá DD, Antonucci A. Cautious classification with data missing not at random using generative random forests [Internet]. Proceedings. 2021 ;[citado 2024 out. 31 ] Available from: https://doi.org/10.1007/978-3-030-86772-0_21
Vancouver
Villanueva Llerena JG, Mauá DD, Antonucci A. Cautious classification with data missing not at random using generative random forests [Internet]. Proceedings. 2021 ;[citado 2024 out. 31 ] Available from: https://doi.org/10.1007/978-3-030-86772-0_21
Trabalho de evento-anais periodico
Two reformulation approaches to maximum-a-posteriori inference in sum-product networks (2020)
Mauá, Denis Deratani ; Ribeiro, Heitor Reis; Katague, Gustavo Perez; Antonucci, Alessandro
Source: Proceedings of Machine Learning Research. Conference titles: International Conference on Probabilistic Graphical Models. Unidade: IME
Subjects: MODELOS PARA PROCESSOS ESTOCÁSTICOS, PROGRAMAÇÃO LINEAR
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MAUÁ, Denis Deratani et al. Two reformulation approaches to maximum-a-posteriori inference in sum-product networks. Proceedings of Machine Learning Research. Brookline: Instituto de Matemática e Estatística, Universidade de São Paulo. Disponível em: https://proceedings.mlr.press/v138/maua20a/maua20a.pdf. Acesso em: 31 out. 2024. , 2020
APA
Mauá, D. D., Ribeiro, H. R., Katague, G. P., & Antonucci, A. (2020). Two reformulation approaches to maximum-a-posteriori inference in sum-product networks. Proceedings of Machine Learning Research. Brookline: Instituto de Matemática e Estatística, Universidade de São Paulo. Recuperado de https://proceedings.mlr.press/v138/maua20a/maua20a.pdf
NLM
Mauá DD, Ribeiro HR, Katague GP, Antonucci A. Two reformulation approaches to maximum-a-posteriori inference in sum-product networks [Internet]. Proceedings of Machine Learning Research. 2020 ; 138 293-304.[citado 2024 out. 31 ] Available from: https://proceedings.mlr.press/v138/maua20a/maua20a.pdf
Vancouver
Mauá DD, Ribeiro HR, Katague GP, Antonucci A. Two reformulation approaches to maximum-a-posteriori inference in sum-product networks [Internet]. Proceedings of Machine Learning Research. 2020 ; 138 293-304.[citado 2024 out. 31 ] Available from: https://proceedings.mlr.press/v138/maua20a/maua20a.pdf
Artigo de periodico
Tractable inference in credal sentential decision diagrams (2020)
Mattei, Lilith; Antonucci, Alessandro; Mauá, Denis Deratani ; Facchini, Alessandro ; Villanueva Llerena, Julissa Giuliana
Source: International Journal of Approximate Reasoning. Unidade: IME
Assunto: MODELOS PARA PROCESSOS ESTOCÁSTICOS
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ABNT
MATTEI, Lilith et al. Tractable inference in credal sentential decision diagrams. International Journal of Approximate Reasoning, v. 125, p. 26-48, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.ijar.2020.06.005. Acesso em: 31 out. 2024.
APA
Mattei, L., Antonucci, A., Mauá, D. D., Facchini, A., & Villanueva Llerena, J. G. (2020). Tractable inference in credal sentential decision diagrams. International Journal of Approximate Reasoning, 125, 26-48. doi:10.1016/j.ijar.2020.06.005
NLM
Mattei L, Antonucci A, Mauá DD, Facchini A, Villanueva Llerena JG. Tractable inference in credal sentential decision diagrams [Internet]. International Journal of Approximate Reasoning. 2020 ; 125 26-48.[citado 2024 out. 31 ] Available from: https://doi.org/10.1016/j.ijar.2020.06.005
Vancouver
Mattei L, Antonucci A, Mauá DD, Facchini A, Villanueva Llerena JG. Tractable inference in credal sentential decision diagrams [Internet]. International Journal of Approximate Reasoning. 2020 ; 125 26-48.[citado 2024 out. 31 ] Available from: https://doi.org/10.1016/j.ijar.2020.06.005
Trabalho de evento
Learning probabilistic sentential decision diagrams by sampling (2020)
Geh, Renato Lui ; Mauá, Denis Deratani ; Antonucci, Alessandro
Source: Proceedings. Conference titles: Symposium on Knowledge Discovery, Mining and Learning - KDMiLe. Unidade: IME
Subjects: INTELIGÊNCIA ARTIFICIAL, APRENDIZADO COMPUTACIONAL, RACIOCÍNIO PROBABILÍSTICO
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ABNT
GEH, Renato Lui e MAUÁ, Denis Deratani e ANTONUCCI, Alessandro. Learning probabilistic sentential decision diagrams by sampling. 2020, Anais.. Porto Alegre: SBC, 2020. Disponível em: https://doi.org/10.5753/kdmile.2020.11968. Acesso em: 31 out. 2024.
APA
Geh, R. L., Mauá, D. D., & Antonucci, A. (2020). Learning probabilistic sentential decision diagrams by sampling. In Proceedings. Porto Alegre: SBC. doi:10.5753/kdmile.2020.11968
NLM
Geh RL, Mauá DD, Antonucci A. Learning probabilistic sentential decision diagrams by sampling [Internet]. Proceedings. 2020 ;[citado 2024 out. 31 ] Available from: https://doi.org/10.5753/kdmile.2020.11968
Vancouver
Geh RL, Mauá DD, Antonucci A. Learning probabilistic sentential decision diagrams by sampling [Internet]. Proceedings. 2020 ;[citado 2024 out. 31 ] Available from: https://doi.org/10.5753/kdmile.2020.11968
Trabalho de evento
Exploring the space of probabilistic sentential decision diagrams (2019)
Mattei, Lilith; Soares, Decio Lauro ; Antonucci, Alessandro ; Mauá, Denis Deratani ; Facchini, Alessandro
Source: Proceedings of Machine Learning Research - PMLR. Conference titles: Workshop on Tractable Probabilistic Modeling - TPM. Unidade: IME
Assunto: MODELOS PARA PROCESSOS ESTOCÁSTICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MATTEI, Lilith et al. Exploring the space of probabilistic sentential decision diagrams. 2019, Anais.. San Diego: International Conference on Machine Learning, 2019. Disponível em: https://drive.google.com/file/d/1PkckPpeLUOP_Oeik_q4MprD6ZJeekqHZ/view. Acesso em: 31 out. 2024.
APA
Mattei, L., Soares, D. L., Antonucci, A., Mauá, D. D., & Facchini, A. (2019). Exploring the space of probabilistic sentential decision diagrams. In Proceedings of Machine Learning Research - PMLR. San Diego: International Conference on Machine Learning. Recuperado de https://drive.google.com/file/d/1PkckPpeLUOP_Oeik_q4MprD6ZJeekqHZ/view
NLM
Mattei L, Soares DL, Antonucci A, Mauá DD, Facchini A. Exploring the space of probabilistic sentential decision diagrams [Internet]. Proceedings of Machine Learning Research - PMLR. 2019 ;[citado 2024 out. 31 ] Available from: https://drive.google.com/file/d/1PkckPpeLUOP_Oeik_q4MprD6ZJeekqHZ/view
Vancouver
Mattei L, Soares DL, Antonucci A, Mauá DD, Facchini A. Exploring the space of probabilistic sentential decision diagrams [Internet]. Proceedings of Machine Learning Research - PMLR. 2019 ;[citado 2024 out. 31 ] Available from: https://drive.google.com/file/d/1PkckPpeLUOP_Oeik_q4MprD6ZJeekqHZ/view
Artigo de periodico
Hidden Markov models with set-valued parameters (2016)
Mauá, Denis Deratani ; Antonucci, Alessandro; Campos, Cassio Polpo de
Source: Neurocomputing. Unidade: IME
Subjects: PROCESSOS DE MARKOV, RECONHECIMENTO DE PADRÕES, ROBUSTEZ
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ABNT
MAUÁ, Denis Deratani e ANTONUCCI, Alessandro e CAMPOS, Cassio Polpo de. Hidden Markov models with set-valued parameters. Neurocomputing, v. 180, p. 94-107, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2015.08.095. Acesso em: 31 out. 2024.
APA
Mauá, D. D., Antonucci, A., & Campos, C. P. de. (2016). Hidden Markov models with set-valued parameters. Neurocomputing, 180, 94-107. doi:10.1016/j.neucom.2015.08.095
NLM
Mauá DD, Antonucci A, Campos CP de. Hidden Markov models with set-valued parameters [Internet]. Neurocomputing. 2016 ; 180 94-107.[citado 2024 out. 31 ] Available from: https://doi.org/10.1016/j.neucom.2015.08.095
Vancouver
Mauá DD, Antonucci A, Campos CP de. Hidden Markov models with set-valued parameters [Internet]. Neurocomputing. 2016 ; 180 94-107.[citado 2024 out. 31 ] Available from: https://doi.org/10.1016/j.neucom.2015.08.095
Trabalho de evento
Early classification of time series by Hidden Markov Models with set-valued parameters (2015)
Antonucci, Alessandro; Mauá, Denis Deratani ; Scanagatta, Mauro; Campos, Cassio Polpo de
Source: Proceedings. Conference titles: NIPS Time Series Workshop 2015. Unidade: IME
Subjects: ANÁLISE DE SÉRIES TEMPORAIS, PROCESSOS DE MARKOV
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ANTONUCCI, Alessandro et al. Early classification of time series by Hidden Markov Models with set-valued parameters. 2015, Anais.. Montreal: NIPS Foundation, 2015. Disponível em: https://drive.google.com/file/d/0Bx7depbNYaFIdjhPNEtsN1pDa2RBWVhPUmxYMURNdmp5a05n/view. Acesso em: 31 out. 2024.
APA
Antonucci, A., Mauá, D. D., Scanagatta, M., & Campos, C. P. de. (2015). Early classification of time series by Hidden Markov Models with set-valued parameters. In Proceedings. Montreal: NIPS Foundation. Recuperado de https://drive.google.com/file/d/0Bx7depbNYaFIdjhPNEtsN1pDa2RBWVhPUmxYMURNdmp5a05n/view
NLM
Antonucci A, Mauá DD, Scanagatta M, Campos CP de. Early classification of time series by Hidden Markov Models with set-valued parameters [Internet]. Proceedings. 2015 ;[citado 2024 out. 31 ] Available from: https://drive.google.com/file/d/0Bx7depbNYaFIdjhPNEtsN1pDa2RBWVhPUmxYMURNdmp5a05n/view
Vancouver
Antonucci A, Mauá DD, Scanagatta M, Campos CP de. Early classification of time series by Hidden Markov Models with set-valued parameters [Internet]. Proceedings. 2015 ;[citado 2024 out. 31 ] Available from: https://drive.google.com/file/d/0Bx7depbNYaFIdjhPNEtsN1pDa2RBWVhPUmxYMURNdmp5a05n/view

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