Hypergraphs as a mean of discovering the dependence structure of a discrete multivariate probability distribution
暂无分享,去创建一个
[1] Enrique F. Castillo,et al. Expert Systems and Probabilistic Network Models , 1996, Monographs in Computer Science.
[2] I. Csiszár. $I$-Divergence Geometry of Probability Distributions and Minimization Problems , 1975 .
[3] András Prékopa,et al. Probability Bounds with Cherry Trees , 2001, Math. Oper. Res..
[4] Luis M. de Campos,et al. A new approach for learning belief networks using independence criteria , 2000, Int. J. Approx. Reason..
[5] Solomon Kullback,et al. Information Theory and Statistics , 1960 .
[6] Thomas M. Cover,et al. Elements of Information Theory , 2005 .
[7] Tamás Szántai,et al. Probability bounds given by hypercherry trees , 2002, Optim. Methods Softw..
[8] David J. Spiegelhalter,et al. Probabilistic Networks and Expert Systems , 1999, Information Science and Statistics.
[9] C. N. Liu,et al. Approximating discrete probability distributions with dependence trees , 1968, IEEE Trans. Inf. Theory.
[10] Jie Cheng,et al. An Algorithm for Bayesian Belief Network Construction from Data , 2004 .
[11] Luis M. de Campos,et al. An Algorithm for Finding Minimum d-Separating Sets in Belief Networks , 1996, UAI.
[12] Tamás Szántai,et al. On the Approximation of a Discrete Multivariate Probability Distribution Using the New Concept of t -Cherry Junction Tree , 2010 .
[13] David J. Spiegelhalter,et al. Local computations with probabilities on graphical structures and their application to expert systems , 1990 .
[14] Mahadev Satyanarayanan,et al. Coping with uncertainty , 2003, IEEE Pervasive Computing.
[15] J. Bukszár. Upper bounds for the probability of a union by multitrees , 2001 .
[16] Tamás Szántai,et al. Application Of t-Cherry Junction Trees in Pattern Recognition , 2010 .
[17] Marek Makowski,et al. Coping with Uncertainty. Modeling and Policy Issues , 2006 .