Using Markov Blankets for Causal Structure Learning
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[1] A. Raveh. On the use of the Inverse of the Correlation Matrix in Multivariate Data Analysis , 1985 .
[2] David J. Spiegelhalter,et al. Local computations with probabilities on graphical structures and their application to expert systems , 1990 .
[3] Judea Pearl,et al. Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.
[4] E. Ziegel. Introduction to the Theory and Practice of Econometrics , 1989 .
[5] Gregory F. Cooper,et al. The ALARM Monitoring System: A Case Study with two Probabilistic Inference Techniques for Belief Networks , 1989, AIME.
[6] Judea Pearl,et al. A Theory of Inferred Causation , 1991, KR.
[7] Ewart R. Carson,et al. A Model-Based Approach to Insulin Adjustment , 1991, AIME.
[8] P. Spirtes,et al. Causation, prediction, and search , 1993 .
[9] Ron Kohavi,et al. Irrelevant Features and the Subset Selection Problem , 1994, ICML.
[10] Christopher Meek,et al. Causal inference and causal explanation with background knowledge , 1995, UAI.
[11] J. Pearl. Causal diagrams for empirical research , 1995 .
[12] A. H. Murphy,et al. Hailfinder: A Bayesian system for forecasting severe weather , 1996 .
[13] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .
[14] Ron Kohavi,et al. Wrappers for Feature Subset Selection , 1997, Artif. Intell..
[15] R Scheines,et al. The TETRAD Project: Constraint Based Aids to Causal Model Specification. , 1998, Multivariate behavioral research.
[16] J. Woodward,et al. Independence, Invariance and the Causal Markov Condition , 1999, The British Journal for the Philosophy of Science.
[17] Sebastian Thrun,et al. Bayesian Network Induction via Local Neighborhoods , 1999, NIPS.
[18] Richard Scheines,et al. Causation, Prediction, and Search, Second Edition , 2000, Adaptive computation and machine learning.
[19] J. Pearl. Causality: Models, Reasoning and Inference , 2000 .
[20] Michal Linial,et al. Using Bayesian Networks to Analyze Expression Data , 2000, J. Comput. Biol..
[21] David Maxwell Chickering,et al. Optimal Structure Identification With Greedy Search , 2002, J. Mach. Learn. Res..
[22] Michael I. Jordan,et al. Learning Graphical Models with Mercer Kernels , 2002, NIPS.
[23] Constantin F. Aliferis,et al. HITON: A Novel Markov Blanket Algorithm for Optimal Variable Selection , 2003, AMIA.
[24] Constantin F. Aliferis,et al. Towards Principled Feature Selection: Relevancy, Filters and Wrappers , 2003 .
[25] Isabelle Guyon,et al. An Introduction to Variable and Feature Selection , 2003, J. Mach. Learn. Res..
[26] Constantin F. Aliferis,et al. Time and sample efficient discovery of Markov blankets and direct causal relations , 2003, KDD '03.
[27] Bernhard Schölkopf,et al. A tutorial on support vector regression , 2004, Stat. Comput..
[28] Constantin F. Aliferis,et al. A theoretical characterization of linear SVM-based feature selection , 2004, ICML '04.
[29] Stuart J. Russell,et al. Adaptive Probabilistic Networks with Hidden Variables , 1997, Machine Learning.
[30] R. Shibata,et al. PARTIAL CORRELATION AND CONDITIONAL CORRELATION AS MEASURES OF CONDITIONAL INDEPENDENCE , 2004 .
[31] Jason Weston,et al. Gene Selection for Cancer Classification using Support Vector Machines , 2002, Machine Learning.
[32] Lawrence D. Fu. A COMPARISON OF STATE-OF-THE-ART ALGORITHMS FOR LEARNING BAYESIAN NETWORK STRUCTURE FROM CONTINUOUS DATA , 2005 .
[33] Jesper Tegnér,et al. Scalable, Efficient and Correct Learning of Markov Boundaries Under the Faithfulness Assumption , 2005, ECSQARU.
[34] Dimitris Margaritis,et al. Distribution-Free Learning of Bayesian Network Structure in Continuous Domains , 2005, AAAI.
[35] D. Hardin,et al. Using SVM Weight-Based Methods to Identify Causally Relevant and Non-Causally Relevant Variables , 2006 .
[36] Constantin F. Aliferis,et al. The max-min hill-climbing Bayesian network structure learning algorithm , 2006, Machine Learning.
[37] Daniel Steel,et al. Homogeneity, selection, and the faithfulness condition , 2006, Minds and Machines.
[38] Jesper Tegnér,et al. Consistent Feature Selection for Pattern Recognition in Polynomial Time , 2007, J. Mach. Learn. Res..
[39] André Elisseeff,et al. A Partial Correlation-Based Algorithm for Causal Structure Discovery with Continuous Variables , 2007, IDA.
[40] Constantin F. Aliferis,et al. Causal Feature Selection , 2007 .