Advances in learning Bayesian networks of bounded treewidth (2014)
- Authors:
- Autor USP: MAUÁ, DENIS DERATANI - IME
- Unidade: IME
- Subjects: ALGORITMOS; INTELIGÊNCIA ARTIFICIAL; ANÁLISE DE ALGORITMOS; TEORIA DOS GRAFOS; COMBINATÓRIA; APRENDIZADO COMPUTACIONAL
- Language: Inglês
- Imprenta:
- Publisher: NIPS Foundation
- Publisher place: Montreal
- Date published: 2014
- Source:
- Conference titles: Annual Conference on Neural Information Processing Systems - NIPS
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ABNT
NIE, Siqi et al. Advances in learning Bayesian networks of bounded treewidth. 2014, Anais.. Montreal: NIPS Foundation, 2014. Disponível em: http://papers.nips.cc/paper/5530-advances-in-learning-bayesian-networks-of-bounded-treewidth.pdf. Acesso em: 21 jan. 2026. -
APA
Nie, S., Mauá, D. D., Campos, C. P. de, & Ji, Q. (2014). Advances in learning Bayesian networks of bounded treewidth. In Advances in Neural Information Processing Systems, 27. Montreal: NIPS Foundation. Recuperado de http://papers.nips.cc/paper/5530-advances-in-learning-bayesian-networks-of-bounded-treewidth.pdf -
NLM
Nie S, Mauá DD, Campos CP de, Ji Q. Advances in learning Bayesian networks of bounded treewidth [Internet]. Advances in Neural Information Processing Systems, 27. 2014 ;[citado 2026 jan. 21 ] Available from: http://papers.nips.cc/paper/5530-advances-in-learning-bayesian-networks-of-bounded-treewidth.pdf -
Vancouver
Nie S, Mauá DD, Campos CP de, Ji Q. Advances in learning Bayesian networks of bounded treewidth [Internet]. Advances in Neural Information Processing Systems, 27. 2014 ;[citado 2026 jan. 21 ] Available from: http://papers.nips.cc/paper/5530-advances-in-learning-bayesian-networks-of-bounded-treewidth.pdf - The National Meeting on Artificial and Computational Intelligence (ENIAC) is one the main national forums for researchers... [Preface]
- Approximation complexity of maximum a posteriori inference in sum-product networks
- Hidden Markov models with set-valued parameters
- Modelos de tópicos na classificação automática de resenhas de usuário
- Advances in automatically solving the ENEM
- Better initialization heuristics for order-based bayesian network structure learning
- Time robust trees: using temporal invariance to improve generalization
- Special issue on robustness in probabilistic graphical models. [Editorial]
- Initialization heuristics for greedy bayesian network structure learning
- International Journal of Approximate Reasoning
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