The complexity of MAP inference in Bayesian networks specified through logical languages (2015)
- Authors:
- USP affiliated authors: MAUÁ, DENIS DERATANI - IME ; COZMAN, FABIO GAGLIARDI - EP
- Unidades: IME; EP
- Subjects: COMPUTABILIDADE E COMPLEXIDADE; INTELIGÊNCIA ARTIFICIAL
- Language: Inglês
- Imprenta:
- Publisher: AAAI Press / International Joint Conferences on Artificial Intelligence
- Publisher place: Palo Alto
- Date published: 2015
- Source:
- Título: Proceedings
- Conference titles: International Joint Conference on Artificial Intelligence - IJCAI
-
ABNT
MAUÁ, Denis Deratani e CAMPOS, Cassio Polpo de e COZMAN, Fabio Gagliardi. The complexity of MAP inference in Bayesian networks specified through logical languages. 2015, Anais.. Palo Alto: AAAI Press / International Joint Conferences on Artificial Intelligence, 2015. Disponível em: http://ijcai.org/papers15/Papers/IJCAI15-130.pdf. Acesso em: 23 jan. 2026. -
APA
Mauá, D. D., Campos, C. P. de, & Cozman, F. G. (2015). The complexity of MAP inference in Bayesian networks specified through logical languages. In Proceedings. Palo Alto: AAAI Press / International Joint Conferences on Artificial Intelligence. Recuperado de http://ijcai.org/papers15/Papers/IJCAI15-130.pdf -
NLM
Mauá DD, Campos CP de, Cozman FG. The complexity of MAP inference in Bayesian networks specified through logical languages [Internet]. Proceedings. 2015 ;[citado 2026 jan. 23 ] Available from: http://ijcai.org/papers15/Papers/IJCAI15-130.pdf -
Vancouver
Mauá DD, Campos CP de, Cozman FG. The complexity of MAP inference in Bayesian networks specified through logical languages [Internet]. Proceedings. 2015 ;[citado 2026 jan. 23 ] Available from: http://ijcai.org/papers15/Papers/IJCAI15-130.pdf - Thirty years of credal networks: specification, algorithms and complexity
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- The descriptive complexity of bayesian network specifications
- Complexity results for probabilistic answer set programming
- On the semantics and complexity of probabilistic logic programs
- Credal sum-product networks
- The effect of combination functions on the complexity of relational Bayesian networks
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