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Volumn , Issue , 2011, Pages 363-372

Noisy-OR models with latent confounding

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; LEARNING ALGORITHMS;

EID: 80053138092     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (9)

References (15)
  • 1
    • 0039630447 scopus 로고    scopus 로고
    • From covariation to causation: A causal power theory
    • Cheng, P. W. (1997). From covariation to causation: A causal power theory. Psychological Review, 104(2):367-405.
    • (1997) Psychological Review , vol.104 , Issue.2 , pp. 367-405
    • Cheng, P.W.1
  • 2
    • 80053140591 scopus 로고    scopus 로고
    • Causal discovery discovery in multiple models from different experiments
    • Claassen, T. and Heskes, T. (2010). Causal discovery discovery in multiple models from different experiments. In NIPS 2010.
    • (2010) NIPS 2010
    • Claassen, T.1    Heskes, T.2
  • 3
    • 0007047929 scopus 로고    scopus 로고
    • Causal discovery from a mixture of experimental and observational data
    • Cooper, G. and Yoo, C. (1999). Causal discovery from a mixture of experimental and observational data. In UAI 1999.
    • (1999) UAI 1999
    • Cooper, G.1    Yoo, C.2
  • 4
    • 80053160158 scopus 로고    scopus 로고
    • Linearity properties of Bayes nets with binary variables
    • Danks, D. and Glymour, C. (2001). Linearity properties of Bayes nets with binary variables. In UAI 2001.
    • (2001) UAI 2001
    • Danks, D.1    Glymour, C.2
  • 6
    • 80053161481 scopus 로고    scopus 로고
    • Combining experiments to discover linear cyclic models with latent variables
    • Eberhardt, F., Hoyer, P. O., and Scheines, R. (2010). Combining experiments to discover linear cyclic models with latent variables. In AISTATS 2010.
    • (2010) AISTATS , vol.2010
    • Eberhardt, F.1    Hoyer, P.O.2    Scheines, R.3
  • 7
    • 0032001389 scopus 로고    scopus 로고
    • Learning causes: Psychological explanations of causal explanation
    • Glymour, C. (1998). Learning causes: Psychological explanations of causal explanation. Minds and Machines, 8:39-60. (Pubitemid 128513020)
    • (1998) Minds and Machines , vol.8 , Issue.1 , pp. 39-60
    • Glymour, C.1
  • 8
    • 34249761849 scopus 로고
    • Learning Bayesian networks: The combination of knowledge and statistical data
    • Heckerman, D., Geiger, D., and Chickering, D. M. (1995). Learning Bayesian networks: The combination of knowledge and statistical data. Machine Learning, 20(3):197-243.
    • (1995) Machine Learning , vol.20 , Issue.3 , pp. 197-243
    • Heckerman, D.1    Geiger, D.2    Chickering, D.M.3
  • 11
    • 46149134436 scopus 로고
    • Fusion, propagation, and structuring in belief networks
    • Pearl, J. (1986). Fusion, propagation, and structuring in belief networks. Artificial Intelligence, 29(3):241-288.
    • (1986) Artificial Intelligence , vol.29 , Issue.3 , pp. 241-288
    • Pearl, J.1
  • 13
    • 0008490311 scopus 로고
    • Plausibility of diagnostic hypotheses
    • Peng, Y. and Reggia, J. (1986). Plausibility of diagnostic hypotheses. In AAAI 1986.
    • (1986) AAAI 1986
    • Peng, Y.1    Reggia, J.2
  • 15
    • 0040731124 scopus 로고
    • Causal inference in the presence of latent variables and selection bias
    • Spirtes, P., Meek, C., and Richardson, T. (1995). Causal inference in the presence of latent variables and selection bias. In UAI 1995.
    • (1995) UAI 1995
    • Spirtes, P.1    Meek, C.2    Richardson, T.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.