ReP USP - Resultado da busca

Artigo de periodico
Better initialization heuristics for order-based bayesian network structure learning (2016)
Urcia, Walter Perez; Mauá, Denis Deratani
Source: Journal of Information and Data Management - JIDM. Unidade: IME
Assunto: INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
URCIA, Walter Perez e MAUÁ, Denis Deratani. Better initialization heuristics for order-based bayesian network structure learning. Journal of Information and Data Management - JIDM, v. 7, n. 2, p. 181-195, 2016Tradução . . Acesso em: 14 nov. 2024.
APA
Urcia, W. P., & Mauá, D. D. (2016). Better initialization heuristics for order-based bayesian network structure learning. Journal of Information and Data Management - JIDM, 7( 2), 181-195.
NLM
Urcia WP, Mauá DD. Better initialization heuristics for order-based bayesian network structure learning. Journal of Information and Data Management - JIDM. 2016 ; 7( 2): 181-195.[citado 2024 nov. 14 ]
Vancouver
Urcia WP, Mauá DD. Better initialization heuristics for order-based bayesian network structure learning. Journal of Information and Data Management - JIDM. 2016 ; 7( 2): 181-195.[citado 2024 nov. 14 ]
Trabalho de evento-anais periodico
The effect of combination functions on the complexity of relational Bayesian networks (2016)
Mauá, Denis Deratani ; Cozman, Fabio Gagliardi
Source: Journal of Machine Learning Research. Conference titles: International Conference on Probabilistic Graphical Models - PMLR. Unidades: EP, IME
Subjects: INFERÊNCIA BAYESIANA, INTELIGÊNCIA ARTIFICIAL, RACIOCÍNIO PROBABILÍSTICO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MAUÁ, Denis Deratani e COZMAN, Fabio Gagliardi. The effect of combination functions on the complexity of relational Bayesian networks. Journal of Machine Learning Research. Brookline: Escola Politécnica, Universidade de São Paulo. Disponível em: http://proceedings.mlr.press/v52/maua16.pdf. Acesso em: 14 nov. 2024. , 2016
APA
Mauá, D. D., & Cozman, F. G. (2016). The effect of combination functions on the complexity of relational Bayesian networks. Journal of Machine Learning Research. Brookline: Escola Politécnica, Universidade de São Paulo. Recuperado de http://proceedings.mlr.press/v52/maua16.pdf
NLM
Mauá DD, Cozman FG. The effect of combination functions on the complexity of relational Bayesian networks [Internet]. Journal of Machine Learning Research. 2016 ;( 52): 333-344.[citado 2024 nov. 14 ] Available from: http://proceedings.mlr.press/v52/maua16.pdf
Vancouver
Mauá DD, Cozman FG. The effect of combination functions on the complexity of relational Bayesian networks [Internet]. Journal of Machine Learning Research. 2016 ;( 52): 333-344.[citado 2024 nov. 14 ] Available from: http://proceedings.mlr.press/v52/maua16.pdf
Artigo de periodico
Equivalences between maximum a posteriori inference in Bayesian networks and maximum expected utility computation in influence diagrams (2016)
Mauá, Denis Deratani
Source: International Journal of Approximate Reasoning. Unidade: IME
Subjects: INTELIGÊNCIA ARTIFICIAL, PROBABILIDADE APLICADA, RACIOCÍNIO PROBABILÍSTICO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MAUÁ, Denis Deratani. Equivalences between maximum a posteriori inference in Bayesian networks and maximum expected utility computation in influence diagrams. International Journal of Approximate Reasoning, v. 68, n. Ja 2016, p. 211-229, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.ijar.2015.03.007. Acesso em: 14 nov. 2024.
APA
Mauá, D. D. (2016). Equivalences between maximum a posteriori inference in Bayesian networks and maximum expected utility computation in influence diagrams. International Journal of Approximate Reasoning, 68( Ja 2016), 211-229. doi:10.1016/j.ijar.2015.03.007
NLM
Mauá DD. Equivalences between maximum a posteriori inference in Bayesian networks and maximum expected utility computation in influence diagrams [Internet]. International Journal of Approximate Reasoning. 2016 ; 68( Ja 2016): 211-229.[citado 2024 nov. 14 ] Available from: https://doi.org/10.1016/j.ijar.2015.03.007
Vancouver
Mauá DD. Equivalences between maximum a posteriori inference in Bayesian networks and maximum expected utility computation in influence diagrams [Internet]. International Journal of Approximate Reasoning. 2016 ; 68( Ja 2016): 211-229.[citado 2024 nov. 14 ] Available from: https://doi.org/10.1016/j.ijar.2015.03.007
Trabalho de evento-anais periodico
Probabilistic graphical models specified by probabilistic logic programs: semantics and complexit (2016)
Cozman, Fabio Gagliardi ; Mauá, Denis Deratani
Source: Journal of Machine Learning Research. Conference titles: International Conference on Probabilistic Graphical Models - PMLR. Unidades: EP, IME
Subjects: LÓGICA MATEMÁTICA, PROBABILIDADE
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
COZMAN, Fabio Gagliardi e MAUÁ, Denis Deratani. Probabilistic graphical models specified by probabilistic logic programs: semantics and complexit. Journal of Machine Learning Research. Brookline: Escola Politécnica, Universidade de São Paulo. Disponível em: http://proceedings.mlr.press/v52/cozman16.pdf. Acesso em: 14 nov. 2024. , 2016
APA
Cozman, F. G., & Mauá, D. D. (2016). Probabilistic graphical models specified by probabilistic logic programs: semantics and complexit. Journal of Machine Learning Research. Brookline: Escola Politécnica, Universidade de São Paulo. Recuperado de http://proceedings.mlr.press/v52/cozman16.pdf
NLM
Cozman FG, Mauá DD. Probabilistic graphical models specified by probabilistic logic programs: semantics and complexit [Internet]. Journal of Machine Learning Research. 2016 ;( 52): 110-121.[citado 2024 nov. 14 ] Available from: http://proceedings.mlr.press/v52/cozman16.pdf
Vancouver
Cozman FG, Mauá DD. Probabilistic graphical models specified by probabilistic logic programs: semantics and complexit [Internet]. Journal of Machine Learning Research. 2016 ;( 52): 110-121.[citado 2024 nov. 14 ] Available from: http://proceedings.mlr.press/v52/cozman16.pdf
Trabalho de evento-anais periodico
The structure and complexity of credal semantics (2016)
Cozman, Fabio Gagliardi ; Mauá, Denis Deratani
Source: CEUR Workshop Proceedings. Conference titles: International Workshop on Probabilistic Logic Programming- PLP. Unidades: EP, IME
Subjects: INTELIGÊNCIA ARTIFICIAL, ANÁLISE MULTIVARIADA, PROGRAMAÇÃO LÓGICA, COMPUTABILIDADE E COMPLEXIDADE
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
COZMAN, Fabio Gagliardi e MAUÁ, Denis Deratani. The structure and complexity of credal semantics. CEUR Workshop Proceedings. Aachen: CEUR Workshop Proceedings. Disponível em: http://ceur-ws.org/Vol-1661/paper-01.pdf. Acesso em: 14 nov. 2024. , 2016
APA
Cozman, F. G., & Mauá, D. D. (2016). The structure and complexity of credal semantics. CEUR Workshop Proceedings. Aachen: CEUR Workshop Proceedings. Recuperado de http://ceur-ws.org/Vol-1661/paper-01.pdf
NLM
Cozman FG, Mauá DD. The structure and complexity of credal semantics [Internet]. CEUR Workshop Proceedings. 2016 ; 1661 3-14.[citado 2024 nov. 14 ] Available from: http://ceur-ws.org/Vol-1661/paper-01.pdf
Vancouver
Cozman FG, Mauá DD. The structure and complexity of credal semantics [Internet]. CEUR Workshop Proceedings. 2016 ; 1661 3-14.[citado 2024 nov. 14 ] Available from: http://ceur-ws.org/Vol-1661/paper-01.pdf
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
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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: 14 nov. 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 nov. 14 ] 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 nov. 14 ] Available from: https://doi.org/10.1016/j.neucom.2015.08.095
Artigo de periodico
Fast local search methods for solving limited memory influence diagrams (2016)
Mauá, Denis Deratani ; Cozman, Fabio Gagliardi
Source: International Journal of Approximate Reasoning. Unidades: IME, EP
Subjects: MODELOS PARA PROCESSOS ESTOCÁSTICOS, INTELIGÊNCIA ARTIFICIAL, PROBABILIDADE APLICADA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MAUÁ, Denis Deratani e COZMAN, Fabio Gagliardi. Fast local search methods for solving limited memory influence diagrams. International Journal of Approximate Reasoning, v. 68, n. Ja 2016, p. 230-245, 2016Tradução . . Disponível em: https://doi.org/10.1016/j.ijar.2015.05.003. Acesso em: 14 nov. 2024.
APA
Mauá, D. D., & Cozman, F. G. (2016). Fast local search methods for solving limited memory influence diagrams. International Journal of Approximate Reasoning, 68( Ja 2016), 230-245. doi:10.1016/j.ijar.2015.05.003
NLM
Mauá DD, Cozman FG. Fast local search methods for solving limited memory influence diagrams [Internet]. International Journal of Approximate Reasoning. 2016 ; 68( Ja 2016): 230-245.[citado 2024 nov. 14 ] Available from: https://doi.org/10.1016/j.ijar.2015.05.003
Vancouver
Mauá DD, Cozman FG. Fast local search methods for solving limited memory influence diagrams [Internet]. International Journal of Approximate Reasoning. 2016 ; 68( Ja 2016): 230-245.[citado 2024 nov. 14 ] Available from: https://doi.org/10.1016/j.ijar.2015.05.003

USP Schools

ReP

Filtros

Subjects