PGM 2008

The Fourth European Workshop on Probabilistic Graphical Models

Online proceedings

Below are the papers that appear in the proceedings (PDF, 6.45 MB) of the workshop. A bib-file for the papers can be found here and an archive with all the papers can be downloaded here (zip, 6.57 MB).
  • John M. Agosta, Thomas R. Gardos and Marek J. Druzdzel. Query-Based Diagnostics. Pages 1--8. PDF.
  • Sourour Ammar, Philippe Leray, Boris Defourny and Louis Wehenkel. High-Dimensional Probability Density Estimation with Randomized Ensembles of Tree Structured Bayesian Networks. Pages 9--16. PDF.
  • Alessandro Antonucci, Marco Zaffalon, Yi Sun and Cassio P. de Campos. Generalized Loopy 2U: A New Algorithm for Approximate Inference in Credal Networks. Pages 17--24. PDF.
  • Manuel Arias and Francisco J. Diez. Carmen: An Open Source Project for Probabilistic Graphical Models. Pages 25--32. PDF.
  • Janneke H. Bolt. Bayesian Networks: the Parental Synergy. Pages 33--40. PDF.
  • A. Cano, M. Gomez-Olmedo and S. Moral. A Score Based Ranking of the Edges for the PC Algorithm. Pages 41--48. PDF.
  • Andres Cano, Andres Masegosa and Serafin Moral. A Bayesian Approach to Estimate Probabilities in Classification Trees. Pages 49--56. PDF.
  • Tao Chen, Nevin L. Zhang and Yi Wang. Efficient Model Evaluation in the Search-Based Approach to Latent Structure Discovery. Pages 57--64. PDF.
  • Barry R. Cobb. Measuring Efficiency in Influence Diagram Models. Pages 65--72. PDF.
  • Jorge Cordero H. and Yifeng Zeng. Attribute Clustering Based on Heuristic Tree Partition. Pages 73--80. PDF.
  • Sergio Rodrigues de Morais and Alex Aussem. A Novel Scalable and Correct Markov Boundary Learning Algorithm Under Faithfulness Condition. Pages 81--88. PDF.
  • Peter R. de Waal. Marginals of DAG-Isomorphic Independence Models. Pages 89--96. PDF.
  • Francisco Elizalde, L. Enrique Sucar, Manuel Luque, Francisco Javier Diez and Alberto Reyes. Policy Explanation in Factored Markov Decision Processes. Pages 97--104. PDF.
  • Antonio Fernandez, Jens D. Nielsen and Antonio Salmeron. Learning Naive Bayes Regression Models from Missing Data Using Mixtures of Truncated Exponentials. Pages 105--112. PDF.
  • Ildiko Flesch and Peter J. F. Lucas. The Probabilistic Interpretation of Model-Based Diagnosis. Pages 113--120. PDF.
  • Olivier C. H. Francois. Efficient Bayesian Network Learning Using EM or Pairwise Deletion. Pages 121--128. PDF.
  • Jose A. Gamez, Juan L. Mateo, Thomas D. Nielsen and Jose M. Puerta. Robust Classification Using Mixtures of Dependency Networks. Pages 129--136. PDF.
  • Jose A. Gamez, Juan L. Mateo and Jose M. Puerta. Towards Consistency in General Dependency Networks. Pages 137--144. PDF.
  • Miguel A. Gomez-Villegas, Paloma Main and Rosario Susi. Sensitivity of Gaussian Bayesian Networks to Inaccuracies in Their Parameters. Pages 145--152. PDF.
  • Finn Verner Jensen. Approximate Representation of Optimal Strategies from Influence Diagrams. Pages 153--159. PDF.
  • Johan Kwisthout. Complexity Results for Enumerating MPE and Partial MAP. Pages 161--168. PDF.
  • Helge Langseth, Thomas D. Nielsen, Rafael Rumi and Antonio Salmeron. Parameter Estimation in Mixtures of Truncated Exponentials. Pages 169--176. PDF.
  • Manuel Luque, Thomas D. Nielsen and Finn V. Jensen. An Anytime Algorithm for Evaluating Unconstrained Influence Diagrams. Pages 177--184. PDF.
  • Paul P. Maaskant and Marek J. Druzdzel. An Independence of Causal Interactions Model for Opposing Influences. Pages 185--192. PDF.
  • Anders L. Madsen. New Methods for Marginalization in Lazy Propagation. Pages 193--200. PDF.
  • Anders L. Madsen. Solving CLQG Influence Diagrams Using Arc-Reversal Operations in a Strong Junction Tree. Pages 201--208. PDF.
  • Tommi Mononen and Petri Myllymaki. Computing the Multinomial Stochastic Complexity in Sub-Linear Time. Pages 209--216. PDF.
  • Jens D. Nielsen, Rafael Rumi and Antonio Salmeron. Structural-EM for Learning PDG Models from Incomplete Data. Pages 217--224. PDF.
  • Mathias Niepert and Dirk Van Gucht. Logical Properties of Stable Conditional Independence. Pages 225--232. PDF.
  • Thorsten J. Ottosen and Finn V. Jensen. A* Wars: The Fight for Improving A* Search for Troubleshooting with Dependent Actions. Pages 233--240. PDF.
  • Silja Renooij and Linda C. van der Gaag. Discrimination and its Sensitivity in Probabilistic Networks. Pages 241--248. PDF.
  • R. Santana, A. Mendiburu and J. A. Lozano. An Empirical Analysis of Loopy Belief Propagation in Three Topologies: Grids, Small-World Networks and Random Graphs. Pages 249--256. PDF.
  • Tomi Silander, Teemu Roos, Petri Kontkanen and Petri Myllymaki. Factorized Normalized Maximum Likelihood Criterion for Learning Bayesian Network Structures. Pages 257--264. PDF.
  • Jim Q. Smith and Alireza Daneshkhah. Large Incomplete Sample Robustness in Bayesian Networks. Pages 265--272. PDF.
  • Federico M. Stefanini. Eliciting Expert Beliefs on the Structure of a Bayesian Network. Pages 273--280. PDF.
  • M. Studeny and J. Vomlel. A Geometric Approach to Learning BN Structures. Pages 281--288. PDF.
  • Nicolaj S\o ndberg-Jeppesen and Finn Verner Jensen. An Influence Diagram Framework for Acting Under Influence by Agents with Unknown Goals. Pages 289--296. PDF.
  • Jiri Vomlel and Petr Savicky. Arithmetic Circuits of the Noisy-Or Models. Pages 297--304. PDF.
  • Yang Xiang and Franklin Hanshar. Tightly and Loosely Coupled Decision Paradigms in Multiagent Expedition. Pages 305--312. PDF.