Learning Bayesian networks from data: An information-theory based approach
暂无分享,去创建一个
David A. Bell | Russell Greiner | Jie Cheng | Weiru Liu | Jonathan Kelly | R. Greiner | Jie Cheng | J. Kelly | D. Bell | Weiru Liu
[1] Marek J. Druzdzel,et al. A Hybrid Anytime Algorithm for the Construction of Causal Models From Sparse Data , 1999, UAI.
[2] R. Greiner,et al. Comparing Bayesian Network Classifiers , 1999, UAI.
[3] Joe Suzuki,et al. Learning Bayesian Belief Networks Based on the MDL Principle : An Efficient Algorithm Using the Branch and Bound Technique , 1999 .
[4] Paul J. Krause,et al. Learning probabilistic networks , 1999, The Knowledge Engineering Review.
[5] David Heckerman,et al. A Tutorial on Learning with Bayesian Networks , 1999, Innovations in Bayesian Networks.
[6] Nir Friedman,et al. The Bayesian Structural EM Algorithm , 1998, UAI.
[7] Lonnie Chrisman,et al. A Roadmap to Research on Bayesian Networks and other Decomposable Probabilistic Models , 1998 .
[8] Dale Schuurmans,et al. Learning Bayesian Nets that Perform Well , 1997, UAI.
[9] Yang Xiang,et al. Exploring Parallelism in Learning Belief Networks , 1997, UAI.
[10] Moninder Singh,et al. Learning Bayesian Networks from Incomplete Data , 1997, AAAI/IAAI.
[11] Huaiyu Zhu. On Information and Sufficiency , 1997 .
[12] Weiru Liu,et al. Learning belief networks from data: an information theory based approach , 1997, CIKM '97.
[13] Thomas S. Richardson,et al. Heuristic Greedy Search Algorithms for Latent Variable Models , 1997, AISTATS.
[14] Paola Sebastiani,et al. Discovering Bayesian Networks in Incomplete Databases , 1997 .
[15] Thomas G. Dietterich. Machine-Learning Research Four Current Directions , 1997 .
[16] Benjamin W. Wah,et al. Editorial: Two Named to Editorial Board of IEEE Transactions on Knowledge and Data Engineering , 1996 .
[17] Nir Friedman,et al. Learning Bayesian Networks with Local Structure , 1996, UAI.
[18] David Maxwell Chickering,et al. Learning Equivalence Classes of Bayesian Network Structures , 1996, UAI.
[19] Dan Geiger,et al. A sufficiently fast algorithm for finding close to optimal junction trees , 1996, UAI.
[20] Luis M. de Campos,et al. An Algorithm for Finding Minimum d-Separating Sets in Belief Networks , 1996, UAI.
[21] Sumit Sarkar,et al. An information theoretic technique to design belief network based expert systems , 1996, Decis. Support Syst..
[22] Wray L. Buntine. A Guide to the Literature on Learning Probabilistic Networks from Data , 1996, IEEE Trans. Knowl. Data Eng..
[23] Sumit Sarkar,et al. Constructing Efficient Belief Network Structures With Expert Provided Information , 1996, IEEE Trans. Knowl. Data Eng..
[24] Christopher Meek,et al. Learning Bayesian Networks with Discrete Variables from Data , 1995, KDD.
[25] Christopher Meek,et al. Strong completeness and faithfulness in Bayesian networks , 1995, UAI.
[26] Christopher Meek,et al. Causal inference and causal explanation with background knowledge , 1995, UAI.
[27] Moninder Singh,et al. Construction of Bayesian network structures from data: A brief survey and an efficient algorithm , 1995, Int. J. Approx. Reason..
[28] Peter Norvig,et al. Artificial Intelligence: A Modern Approach , 1995 .
[29] D. Madigan,et al. Model Selection and Accounting for Model Uncertainty in Graphical Models Using Occam's Window , 1994 .
[30] Wai Lam,et al. LEARNING BAYESIAN BELIEF NETWORKS: AN APPROACH BASED ON THE MDL PRINCIPLE , 1994, Comput. Intell..
[31] Wray L. Buntine. Operations for Learning with Graphical Models , 1994, J. Artif. Intell. Res..
[32] Uffe Kjærulff,et al. Reduction of Computational Complexity in Bayesian Networks Through Removal of Weak Dependences , 1994, UAI.
[33] Remco R. Bouckaert,et al. Properties of Bayesian Belief Network Learning Algorithms , 1994, UAI.
[34] Peter Cheeseman,et al. Selecting Models from Data: Artificial Intelligence and Statistics IV , 1994 .
[35] Richard Scheines,et al. TETRAD II: Tools for Discovery , 1994 .
[36] S. K. Wong,et al. Learning Conditional Independence Relations from a Probabilistic Model , 1994 .
[37] Yang Xiang,et al. CONSTRUCTION OF A MARKOV NETWORK FROM DATA FOR PROBABILISTIC INFERENCE , 1994 .
[38] Russell G. Almond,et al. Strategies for Graphical Model Selection , 1994 .
[39] J. Pearl,et al. Logical and Algorithmic Properties of Conditional Independence and Graphical Models , 1993 .
[40] David J. Spiegelhalter,et al. Bayesian analysis in expert systems , 1993 .
[41] Franz von Kutschera,et al. Causation , 1993, J. Philos. Log..
[42] P. Spirtes,et al. Causation, prediction, and search , 1993 .
[43] S. Orbom,et al. When Can Association Graphs Admit A Causal Interpretation? , 1993 .
[44] Judea Pearl,et al. An Algorithm for Deciding if a Set of Observed Independencies Has a Causal Explanation , 1992, UAI.
[45] J. Badsberg. Model Search in Contingency Tables by CoCo , 1992 .
[46] P. Spirtes,et al. An Algorithm for Fast Recovery of Sparse Causal Graphs , 1991 .
[47] Richard E. Neapolitan,et al. Probabilistic reasoning in expert systems - theory and algorithms , 2012 .
[48] Franz Josef Radermacher,et al. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference (Judea Pearl) , 1990, SIAM Rev..
[49] L. N. Kanal,et al. Uncertainty in Artificial Intelligence 5 , 1990 .
[50] Stuart L. Crawford,et al. Constructor: A System for the Induction of Probabilistic Models , 1990, AAAI.
[51] Judea Pearl,et al. Equivalence and Synthesis of Causal Models , 1990, UAI.
[52] David Heckerman,et al. Separable and Transitive Graphoids , 1990, UAI.
[53] Terrance E. Boult,et al. Pruning bayesian networks for efficient computation , 1990, UAI.
[54] Gregory F. Cooper,et al. An Entropy-driven System for Construction of Probabilistic Expert Systems from Databases , 1990, UAI.
[55] Alice M. Agogino,et al. Automated Construction of Sparse Bayesian Networks from Unstructured Probabilistic Models and Domain Information , 2013, UAI.
[56] Judea Pearl,et al. Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.
[57] Gregory F. Cooper,et al. The ALARM Monitoring System: A Case Study with two Probabilistic Inference Techniques for Belief Networks , 1989, AIME.
[58] P. Spirtes,et al. Causality From Probability , 1989 .
[59] David Heckerman,et al. An empirical comparison of three inference methods , 2013, UAI.
[60] David J. Spiegelhalter,et al. Local computations with probabilities on graphical structures and their application to expert systems , 1990 .
[61] Max Henrion,et al. An Experimental Comparison of Knowledge Engineering for Expert Systems and for Decision Analysis , 1987, AAAI.
[62] Judea Pearl,et al. The recovery of causal poly-trees from statistical data , 1987, Int. J. Approx. Reason..
[63] Max Henrion,et al. Propagating uncertainty in bayesian networks by probabilistic logic sampling , 1986, UAI.
[64] N. Wermuth,et al. Graphical and recursive models for contingency tables , 1983 .
[65] C. Glymour. Causal Inference and Causal Explanation , 1982 .
[66] Nils J. Nilsson,et al. Artificial Intelligence , 1974, IFIP Congress.
[67] C. N. Liu,et al. Approximating discrete probability distributions with dependence trees , 1968, IEEE Trans. Inf. Theory.
[68] J. Meigs,et al. WHO Technical Report , 1954, The Yale Journal of Biology and Medicine.