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Volumn , Issue , 2002, Pages

Distribution of mutual information

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN FRAMEWORKS; BAYESIAN NETS; JOINT PROBABILITY; MUTUAL INFORMATIONS; PRIOR DISTRIBUTION; PRIOR INFORMATION; SAMPLING FREQUENCIES; SECOND ORDERS;

EID: 84899012896     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (41)

References (11)
  • 2
    • 0000675167 scopus 로고    scopus 로고
    • Structure learning in conditional probability models VIA an entropic prior and parameter extinction
    • Bra99
    • [Bra99] M. Brand. Structure learning in conditional probability models via an entropic prior and parameter extinction. Neural Computation, 11(5):1155-1182, 1999.
    • (1999) Neural Computation , vol.11 , Issue.5 , pp. 1155-1182
    • Brand, M.1
  • 3
    • 0030124955 scopus 로고    scopus 로고
    • A guide to the literature on learning probabilistic networks from data
    • Bun96
    • [Bun96] W. Buntine. A guide to the literature on learning probabilistic networks from data. IEEE Transactions on Knowledge and Data Engineering, 8:195-210, 1996.
    • (1996) IEEE Transactions on Knowledge and Data Engineering , vol.8 , pp. 195-210
    • Buntine, W.1
  • 4
    • 84889281816 scopus 로고
    • CT91. Wiley Series in Telecommunications. John Wiley & Sons, New York, NY, USA
    • [CT91] T. M. Cover and J. A. Thomas. Elements of Information Theory. Wiley Series in Telecommunications. John Wiley & Sons, New York, NY, USA, 1991.
    • (1991) Elements of Information Theory
    • Cover, T.M.1    Thomas, J.A.2
  • 6
    • 0002370418 scopus 로고    scopus 로고
    • A tutorial on learning with bayesian networks
    • Hec98
    • [Hec98] D. Heckerman. A tutorial on learning with Bayesian networks. Learnig in Graphical Models, pages 301-354, 1998.
    • (1998) Learnig in Graphical Models , pp. 301-354
    • Heckerman, D.1
  • 8
    • 0142140756 scopus 로고    scopus 로고
    • The posterior probability of bayes nets with strong dependences
    • Kle99
    • [Kle99] G. D. Kleiter. The posterior probability of Bayes nets with strong dependences. Soft Computing, 3:162-173, 1999.
    • (1999) Soft Computing , vol.3 , pp. 162-173
    • Kleiter, G.D.1
  • 11
    • 84898984877 scopus 로고
    • Estimating functions of distributions from a finite set of samples, part 2: Bayes estimators for mutual information, chi- squared, covariance and other statistics
    • WW93, Los Alamos National Laboratory, Also Santa Pe Insitute report SFI-TR-93-07-047
    • [WW93] D. R. Wolf and D. H. Wolpert. Estimating functions of distributions from A finite set of samples, part 2: Bayes estimators for mutual information, chi- squared, covariance and other statistics. Technical Report LANL-LA-UR-93- 833, Los Alamos National Laboratory, 1993. Also Santa Pe Insitute report SFI-TR-93-07-047.
    • (1993) Technical Report LANL-LA-UR-93- 833
    • Wolf, D.R.1    Wolpert, D.H.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.