Semantics and Inference for Recursive Probability Models

Proceedings of the 17th National Conference on Artificial Intelligence and 12th Conference on Innovative Applications of Artificial Intelligence, AAAI 2000

Volumn , Issue , 2000, Pages 538-544

  Pfeffer, Avi ^a   Koller, Daphne ^b  

^a HARVARD UNIVERSITY   (United States)

^b Stanford University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

INFERENCE ENGINES; SEMANTICS;

BAYESIA N NETWORKS; EXPRESSIVE POWER; GENETIC MODELS; INFERENCE ALGORITHM; LANGUAGE MODEL; MEASURE-THEORETIC SEMANTICS; PROBABILISTIC INFERENCE; PROBABILITY MODELLING; RELATIONAL MODELING; REPRESENTATION LANGUAGES;

BAYESIAN NETWORKS;

EID: 84880903471     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (10)

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5. Koller, D.; McAllester, D.; and Pfeffer, A. 1997. Effective Bayesian inference for stochastic programs. In Proc. AAAI.
6. Ngo, L., and Haddawy, P. 1996. Answering queries from context-sensitive probabilistic knowledge bases. Theoretical Computer Science.
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8. Pfeffer, A.; Koller, D.; Milch, B.; and Takusagawa, K. 1999. SPOOK: A system for probabilistic object-oriented knowledge representation. In Proc. UAI.
9. Pfeffer, A. 2000. Probabilistic Reasoning for Complex Systems. Ph.D. Dissertation, Stanford University.
10. Wellman, M.; Breese, J.; and Goldman, R. 1992. From knowledge bases to decision models. The Knowledge Engineering Review 7(1):35-53.