메뉴 건너뛰기




Volumn 21, Issue 3, 2007, Pages 295-331

Exact and approximate inference in ProBT

Author keywords

Approximate inference; Bayesian networks; Exact inference; Optimization

Indexed keywords

APPROXIMATION THEORY; BAYESIAN NETWORKS; COMPUTER SIMULATION; MONTE CARLO METHODS; OPTIMIZATION; PROBABILITY DISTRIBUTIONS;

EID: 34548201777     PISSN: 0992499X     EISSN: None     Source Type: Journal    
DOI: 10.3166/ria.21.295-332     Document Type: Article
Times cited : (17)

References (45)
  • 1
    • 0002003951 scopus 로고
    • Linear time algorithms for NP-hard problems restricted to partial k-trees
    • Arnborg S., Proskurowski A., " Linear time algorithms for NP-hard problems restricted to partial k-trees", Discrete and Applied Mathematics, vol. 23, n°1, p. 11-24, 1989.
    • (1989) Discrete and Applied Mathematics , vol.23 , Issue.N1 , pp. 11-24
    • Arnborg, S.1    Proskurowski, A.2
  • 2
    • 0035121292 scopus 로고    scopus 로고
    • A sufficiently fast algorithm for finding close to optimal clique trees
    • Becker A., Geiger D., " A sufficiently fast algorithm for finding close to optimal clique trees", Artificial Intelligence, vol. 125, n° 1-2, p. 3-17, 2001.
    • (2001) Artificial Intelligence , vol.125 , Issue.1-2 , pp. 3-17
    • Becker, A.1    Geiger, D.2
  • 3
    • 0001541731 scopus 로고
    • chapter A note on the generation of random normal deviates, p
    • Box G. E. P., Muller M. E., Annals Math. Stat., vol. 29, chapter A note on the generation of random normal deviates, p. 610-611, 1958.
    • (1958) Annals Math. Stat , vol.29 , pp. 610-611
    • Box, G.E.P.1    Muller, M.E.2
  • 4
    • 0025401005 scopus 로고
    • The computational complexity of probabilistic inference using Bayesian belief networks
    • Cooper G., "The computational complexity of probabilistic inference using Bayesian belief networks", Artificial Intelligence, vol. 42, p. 393-405, 1990.
    • (1990) Artificial Intelligence , vol.42 , pp. 393-405
    • Cooper, G.1
  • 5
    • 0023416976 scopus 로고
    • Minimizing Multimodal Functions of Continuous Variables with the' Simulated Annealing' Algorithm
    • Corana A., Martini C., Ridella S., "Minimizing Multimodal Functions of Continuous Variables with the' Simulated Annealing' Algorithm", ACM Transactions on Mathematical Software, vol. 13, p. 262-280, 1987.
    • (1987) ACM Transactions on Mathematical Software , vol.13 , pp. 262-280
    • Corana, A.1    Martini, C.2    Ridella, S.3
  • 8
    • 0035250750 scopus 로고    scopus 로고
    • Recursive Conditioning
    • Darwiche A., " Recursive Conditioning", Artificial Intelligence, vol. 126, n° 1-2, p. 5-41, 2001.
    • (2001) Artificial Intelligence , vol.126 , Issue.1-2 , pp. 5-41
    • Darwiche, A.1
  • 9
    • 0006504636 scopus 로고    scopus 로고
    • Query DAGs: A Practical Paradigm for Implementing Belief Network Inference
    • Darwiche A., Prován G., " Query DAGs: A Practical Paradigm for Implementing Belief Network Inference", J. Artif. Intellig. Res. (JAIR), vol. 6, p. 147-176, 1997.
    • (1997) J. Artif. Intellig. Res. (JAIR) , vol.6 , pp. 147-176
    • Darwiche, A.1    Prován, G.2
  • 10
    • 0002251094 scopus 로고    scopus 로고
    • Bucket elimination: A unifying framework for probabilistic inference
    • E. Horvits, F. Jensen eds, Portland, Oregon, p
    • Dechter R., "Bucket elimination: A unifying framework for probabilistic inference", in E. Horvits, F. Jensen (eds), Proc. of the Twelveth Conf. on Uncertainty in Artificial Intelligence, Portland, Oregon, p. 211-219, 1996.
    • (1996) Proc. of the Twelveth Conf. on Uncertainty in Artificial Intelligence , pp. 211-219
    • Dechter, R.1
  • 11
    • 0033188982 scopus 로고    scopus 로고
    • Bucket elimination: A unifying framework for probabilistic inference
    • Dechter R., " Bucket elimination: A unifying framework for probabilistic inference", Artificial Intelligence, vol. 113, n° 1-2, p. 41-85, 1999.
    • (1999) Artificial Intelligence , vol.113 , Issue.1-2 , pp. 41-85
    • Dechter, R.1
  • 16
    • 70350097459 scopus 로고    scopus 로고
    • Monte Carlo simulation and numerical integration
    • H. Amman, D. Kendrick, J. Rust eds, Elsevier North-Holland, Amsterdam, p
    • Geweke J., " Monte Carlo simulation and numerical integration", in H. Amman, D. Kendrick, J. Rust (eds), Handbook of Computational Economics, vol. 13, Elsevier North-Holland, Amsterdam, p. 731-800, 1996.
    • (1996) Handbook of Computational Economics , vol.13 , pp. 731-800
    • Geweke, J.1
  • 18
    • 0033330288 scopus 로고    scopus 로고
    • Variational probabilistic inference and the QMR-DT network
    • Jaakkola T. S., Jordan M. I., "Variational probabilistic inference and the QMR-DT network", J. Artif. Intellig. Res. (JAIR), vol. 10, p. 291-322, 1999.
    • (1999) J. Artif. Intellig. Res. (JAIR) , vol.10 , pp. 291-322
    • Jaakkola, T.S.1    Jordan, M.I.2
  • 22
    • 0005056882 scopus 로고    scopus 로고
    • The fast calculation of form factors using low discrepancy point sequence
    • Bratislava, p
    • Keller A., "The fast calculation of form factors using low discrepancy point sequence", Proc. of the 12th Spring Conf. on Computer Graphics, Bratislava, p. 195-204, 1996.
    • (1996) Proc. of the 12th Spring Conf. on Computer Graphics , pp. 195-204
    • Keller, A.1
  • 23
    • 0008091392 scopus 로고
    • Triangulation of graphs - algorithms giving small total state space
    • Technical Report no R 90-09, Dept. of Mathematics and Computer Science, Aalborg University
    • Kjaerulff U., Triangulation of graphs - algorithms giving small total state space, Technical Report no R 90-09, Dept. of Mathematics and Computer Science, Aalborg University, 1990.
    • (1990)
    • Kjaerulff, U.1
  • 24
    • 0001006209 scopus 로고
    • Local computations with probabilities on graphical structures and their applications to expert systems
    • in B, p
    • Lauritzen S. L., Spiegelhalter D. J., " Local computations with probabilities on graphical structures and their applications to expert systems", Proc. of the Royal Statistical Society, n 50 in B, p. 154-227, 1988.
    • (1988) Proc. of the Royal Statistical Society , Issue.50 , pp. 154-227
    • Lauritzen, S.L.1    Spiegelhalter, D.J.2
  • 25
    • 0028466297 scopus 로고
    • Efficient Inference in Bayes Networks As A Combinatorial Optimization Problem
    • Li Z., D'Ambrosio B., " Efficient Inference in Bayes Networks As A Combinatorial Optimization Problem", Int. J. of Approximate Reasoning, vol. 11, p. 55-81, 1994.
    • (1994) Int. J. of Approximate Reasoning , vol.11 , pp. 55-81
    • Li, Z.1    D'Ambrosio, B.2
  • 26
    • 34548258097 scopus 로고    scopus 로고
    • MacKay D. G. C., Introduction to Monte Carlo Methods, Proc. of an Erice summer school, ed. M.Jordan, 1996.
    • MacKay D. G. C., " Introduction to Monte Carlo Methods", Proc. of an Erice summer school, ed. M.Jordan, 1996.
  • 32
    • 0004087397 scopus 로고
    • Probabilistic inference using Markov Chain Monte Carlo methods
    • no CRG-TR-93-1, Dept. of Computer Science, University of Toronto
    • Neal R. M., Probabilistic inference using Markov Chain Monte Carlo methods, Research Report no CRG-TR-93-1, Dept. of Computer Science, University of Toronto, 1993.
    • (1993) Research Report
    • Neal, R.M.1
  • 34
    • 0020276268 scopus 로고
    • Reverand Bayes on inference engines: A distributed hierarchical approach
    • Pittsburgh, p
    • Pearl J., " Reverand Bayes on inference engines: A distributed hierarchical approach", Proc. of the AAAINational Conference on AI, Pittsburgh, p. 133-136, 1982.
    • (1982) Proc. of the AAAINational Conference on AI , pp. 133-136
    • Pearl, J.1
  • 37
    • 0002848005 scopus 로고
    • Graph minors. XIII. The disjoint paths problem
    • Robertson N., Seymour P. D., " Graph minors. XIII. The disjoint paths problem", Journal of Combinatorial Theory, vol. 63, no B, p. 65-110, 1995.
    • (1995) Journal of Combinatorial Theory , vol.63 , Issue.B , pp. 65-110
    • Robertson, N.1    Seymour, P.D.2
  • 38
    • 0014928358 scopus 로고
    • Triangulated graphs and the elimination process
    • Rose D. J., " Triangulated graphs and the elimination process", Journal of Mathematical Analysis and Applications, vol. 32, no 3, p. 597-609, 1970.
    • (1970) Journal of Mathematical Analysis and Applications , vol.32 , Issue.3 , pp. 597-609
    • Rose, D.J.1
  • 40
    • 34548227226 scopus 로고    scopus 로고
    • Shenoy P., Shafer G., Uncertainty in Al, 4, R. Shachter et al, chapter Axioms for Probability and Belief-Function Propagation, 1990.
    • Shenoy P., Shafer G., Uncertainty in Al, vol. 4, R. Shachter et al, chapter Axioms for Probability and Belief-Function Propagation, 1990.
  • 41
    • 0001862169 scopus 로고    scopus 로고
    • A practical algorithm for finding optimal triangulations
    • Shokhet K., Geiger D., " A practical algorithm for finding optimal triangulations", Proc. of AAAI'97, p. 187-190, 1997.
    • (1997) Proc. of AAAI'97 , pp. 187-190
    • Shokhet, K.1    Geiger, D.2
  • 43
    • 0003053548 scopus 로고
    • Bayesian computation via the Gibbs sampler and related Monte Carlo methods
    • Smith A. F., Roberts G. O., " Bayesian computation via the Gibbs sampler and related Monte Carlo methods", Journal of the Royal Statistical Society B, vol. 55, p. 3-23, 1993.
    • (1993) Journal of the Royal Statistical Society B , vol.55 , pp. 3-23
    • Smith, A.F.1    Roberts, G.O.2
  • 44
    • 33748255514 scopus 로고    scopus 로고
    • Importance Sampling Algorithms for Bayesian Networks: Principles and Performance
    • Yuan C., Druzdzel M. J., " Importance Sampling Algorithms for Bayesian Networks: Principles and Performance", Mathematical and Computer Modeling, vol. 43, p. 1189-1207, 2006.
    • (2006) Mathematical and Computer Modeling , vol.43 , pp. 1189-1207
    • Yuan, C.1    Druzdzel, M.J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.