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Artigo de periodico
The joy of probabilistic answer set programming: semantics, complexity, expressivity, inference (2020)
Cozman, Fabio Gagliardi ; Mauá, Denis Deratani
Fonte: International Journal of Approximate Reasoning. Unidades: EP, IME
Assuntos: 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 joy of probabilistic answer set programming: semantics, complexity, expressivity, inference. International Journal of Approximate Reasoning, v. 125, p. 218-239, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.ijar.2020.07.004. Acesso em: 23 nov. 2025.
APA
Cozman, F. G., & Mauá, D. D. (2020). The joy of probabilistic answer set programming: semantics, complexity, expressivity, inference. International Journal of Approximate Reasoning, 125, 218-239. doi:10.1016/j.ijar.2020.07.004
NLM
Cozman FG, Mauá DD. The joy of probabilistic answer set programming: semantics, complexity, expressivity, inference [Internet]. International Journal of Approximate Reasoning. 2020 ; 125 218-239.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1016/j.ijar.2020.07.004
Vancouver
Cozman FG, Mauá DD. The joy of probabilistic answer set programming: semantics, complexity, expressivity, inference [Internet]. International Journal of Approximate Reasoning. 2020 ; 125 218-239.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1016/j.ijar.2020.07.004
Artigo de periodico
Speeding up parameter and rule learning for acyclic probabilistic logic programs (2019)
Faria, Francisco Henrique Otte Vieira de ; Gusmão, Arthur Colombini ; De Bona, Glauber ; Mauá, Denis Deratani ; Cozman, Fabio Gagliardi
Fonte: International Journal of Approximate Reasoning. Unidades: EP, IME
Assuntos: PROGRAMAÇÃO LÓGICA, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FARIA, Francisco Henrique Otte Vieira de et al. Speeding up parameter and rule learning for acyclic probabilistic logic programs. International Journal of Approximate Reasoning, v. 106, p. 32-50, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.ijar.2018.12.012. Acesso em: 23 nov. 2025.
APA
Faria, F. H. O. V. de, Gusmão, A. C., De Bona, G., Mauá, D. D., & Cozman, F. G. (2019). Speeding up parameter and rule learning for acyclic probabilistic logic programs. International Journal of Approximate Reasoning, 106, 32-50. doi:10.1016/j.ijar.2018.12.012
NLM
Faria FHOV de, Gusmão AC, De Bona G, Mauá DD, Cozman FG. Speeding up parameter and rule learning for acyclic probabilistic logic programs [Internet]. International Journal of Approximate Reasoning. 2019 ; 106 32-50.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1016/j.ijar.2018.12.012
Vancouver
Faria FHOV de, Gusmão AC, De Bona G, Mauá DD, Cozman FG. Speeding up parameter and rule learning for acyclic probabilistic logic programs [Internet]. International Journal of Approximate Reasoning. 2019 ; 106 32-50.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1016/j.ijar.2018.12.012
Trabalho de evento
Autotuning high-level synthesis for FPGAs using OpenTuner and LegUp (2018)
Bruel, Pedro; Goldman, Alfredo ; Chalamalasetti, Sai Rahul; Milojicic, Dejan
Fonte: Proceedings. Nome do evento: International Conference on Reconfigurable Computing and FPGAs - ReConFig. Unidade: IME
Assuntos: PROGRAMAÇÃO LÓGICA, HARDWARE
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BRUEL, Pedro et al. Autotuning high-level synthesis for FPGAs using OpenTuner and LegUp. 2018, Anais.. Piscataway: IEEE, 2018. Disponível em: https://doi.org/10.1109/RECONFIG.2017.8279778. Acesso em: 23 nov. 2025.
APA
Bruel, P., Goldman, A., Chalamalasetti, S. R., & Milojicic, D. (2018). Autotuning high-level synthesis for FPGAs using OpenTuner and LegUp. In Proceedings. Piscataway: IEEE. doi:10.1109/RECONFIG.2017.8279778
NLM
Bruel P, Goldman A, Chalamalasetti SR, Milojicic D. Autotuning high-level synthesis for FPGAs using OpenTuner and LegUp [Internet]. Proceedings. 2018 ;[citado 2025 nov. 23 ] Available from: https://doi.org/10.1109/RECONFIG.2017.8279778
Vancouver
Bruel P, Goldman A, Chalamalasetti SR, Milojicic D. Autotuning high-level synthesis for FPGAs using OpenTuner and LegUp [Internet]. Proceedings. 2018 ;[citado 2025 nov. 23 ] Available from: https://doi.org/10.1109/RECONFIG.2017.8279778
Artigo de periodico
On the semantics and complexity of probabilistic logic programs (2017)
Cozman, Fabio Gagliardi ; Mauá, Denis Deratani
Fonte: Journal of Artificial Intelligence Research. Unidades: EP, IME
Assuntos: PROGRAMAÇÃO LÓGICA, PROBABILIDADE
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
COZMAN, Fabio Gagliardi e MAUÁ, Denis Deratani. On the semantics and complexity of probabilistic logic programs. Journal of Artificial Intelligence Research, v. 60, p. 221-262, 2017Tradução . . Disponível em: https://doi.org/10.1613/jair.5482. Acesso em: 23 nov. 2025.
APA
Cozman, F. G., & Mauá, D. D. (2017). On the semantics and complexity of probabilistic logic programs. Journal of Artificial Intelligence Research, 60, 221-262. doi:10.1613/jair.5482
NLM
Cozman FG, Mauá DD. On the semantics and complexity of probabilistic logic programs [Internet]. Journal of Artificial Intelligence Research. 2017 ; 60 221-262.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1613/jair.5482
Vancouver
Cozman FG, Mauá DD. On the semantics and complexity of probabilistic logic programs [Internet]. Journal of Artificial Intelligence Research. 2017 ; 60 221-262.[citado 2025 nov. 23 ] Available from: https://doi.org/10.1613/jair.5482
Trabalho de evento
Closed-form solutions in learning probabilistic logic programs by exact score maximization (2017)
Faria, Francisco Henrique Otte Vieira de ; Cozman, Fabio Gagliardi ; Mauá, Denis Deratani
Fonte: Proceedings. Nome do evento: International Conference on Scalable Uncertainty Management - SUM. Unidades: EP, IME
Assuntos: PROGRAMAÇÃO LÓGICA, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
FARIA, Francisco Henrique Otte Vieira de e COZMAN, Fabio Gagliardi e MAUÁ, Denis Deratani. Closed-form solutions in learning probabilistic logic programs by exact score maximization. 2017, Anais.. Cham: Springer, 2017. Disponível em: https://doi.org/10.1007/978-3-319-67582-4_9. Acesso em: 23 nov. 2025.
APA
Faria, F. H. O. V. de, Cozman, F. G., & Mauá, D. D. (2017). Closed-form solutions in learning probabilistic logic programs by exact score maximization. In Proceedings. Cham: Springer. doi:10.1007/978-3-319-67582-4_9
NLM
Faria FHOV de, Cozman FG, Mauá DD. Closed-form solutions in learning probabilistic logic programs by exact score maximization [Internet]. Proceedings. 2017 ;[citado 2025 nov. 23 ] Available from: https://doi.org/10.1007/978-3-319-67582-4_9
Vancouver
Faria FHOV de, Cozman FG, Mauá DD. Closed-form solutions in learning probabilistic logic programs by exact score maximization [Internet]. Proceedings. 2017 ;[citado 2025 nov. 23 ] Available from: https://doi.org/10.1007/978-3-319-67582-4_9

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