Advanced Methodologies for Bayesian Networks: Second International Workshop, AMBN 2015, Yokohama, Japan, November 16-18, 2015. Proceedings (Lecture Notes in Computer Science Book 9505)

This volume constitutes the refereed proceedings of the Second International Workshop on Advanced Methodologies for Bayesian Networks, AMBN 2015, held in Yokohama, Japan, in November 2015. The 18 revised full papers and 6 invited abstracts presented were carefully reviewed and selected from numerous submissions. In the International Workshop on Advanced Methodologies for Bayesian Networks (AMBN), the researchers explore methodologies for enhancing the effectiveness of graphical models including modeling, reasoning, model selection, logic-probability relations, and causality. The exploration of methodologies is complemented discussions of practical considerations for applying graphical models in real world settings, covering concerns like scalability, incremental learning, parallelization, and so on. Front Matter....Pages I-XVIII Efficiently Learning Bayesian Network Structures Based on the B&B Strategy: A Theoretical Analysis....Pages 1-14 Constraint-Based Learning Bayesian Networks Using Bayes Factor....Pages 15-31 Learning Bayesian Network Parameters from Small Data Set: A Spatially Maximum a Posteriori Method....Pages 32-45 Hashing-Based Hybrid Duplicate Detection for Bayesian Network Structure Learning....Pages 46-60 A Bayesian Network Approach for Predicting Purchase Behavior via Direct Observation of In-store Behavior....Pages 61-75 Statistical Tests for Joint Analysis of Performance Measures....Pages 76-92 Extending Naive Bayes Classifier with Hierarchy Feature Level Information for Record Linkage....Pages 93-104 Empirical Behavior of Bayesian Network Structure Learning Algorithms....Pages 105-121 On Model Selection, Bayesian Networks, and the Fisher Information Integral....Pages 122-135 Unsupervised Evolutionary Algorithm for Dynamic Bayesian Network Structure Learning....Pages 136-151 A Fast Clique Maintenance Algorithm for Optimal Triangulation of Bayesian Networks....Pages 152-167 Factorization of ZDDs for Representing Bayesian Networks Based on d-Separations....Pages 168-183 Missing Data from a Causal Perspective....Pages 184-195 Learning Maximal Ancestral Graphs with Robustness for Faithfulness Violations....Pages 196-208 Discriminative and Generative Models in Causal and Anticausal Settings....Pages 209-221 A Non-Gaussian Approach for Causal Discovery in the Presence of Hidden Common Causes....Pages 222-233 Forest Learning Based on the Chow-Liu Algorithm and Its Application to Genome Differential Analysis: A Novel Mutual Information Estimation....Pages 234-249 Tips and Tricks for Building Bayesian Networks for Scoring Game-Based Assessments....Pages 250-263 Back Matter....Pages 265-265