PGM 2002: Cuenca, Spain

• David Allen, Adnan Darwiche:
  Optimal Time-Space Tradeoff in Probabilistic Inference.
  
• Rosa Blanco, Iñaki Inza, Pedro Larrañaga:
  Floating Search Methods in Learning Bayesian Networks.
  
• Robert Castelo, Michael D. Perlman:
  Learning Essential Graph Markov Models From Data.
  
• Alireza Daneshkhah, Jim Q. Smith:
  Multicausal Prior Families, Randomisation and Essential Graphs.
  
• Luis M. de Campos, Juan M. Fernández-Luna, Juan F. Huete:
  Reducing Propagation Effort in Large Polytrees: An Application to Information Retrieval.
  
• Luis M. de Campos, José A. Gámez, Jose Miguel Puerta:
  Graphical Models to Causal Discovery from Data.
  
• Murat Deviren, Khalid Daoudi:
  Continuous Speech Recognition Using Dynamic Bayesian Networks. A Fast Decoding Algorithm.
  
• Juan A. Fernández del Pozo, Concha Bielza:
  New Structures for Conditional Probability Tables.
  
• Mark Hopkins, Adnan Darwiche:
  A Practical Relaxation of Constant-Factor Treewidth Approximation Algorithms.
  
• Manfred Jaeger:
  Probabilistic Decision Graphs - Combining Verification and AI Techniques for Probabilistic Inference.
  
• Kristian Kersting, Niels Landwehr:
  Scaled Conjugate Gradients for Maximum Likelihood: An Empirical Comparison with the EM Algorithm.
  
• Kristian Kersting, Tapani Raiko, Luc De Raedt:
  Logical Hidden Markov Models (Extendes abstract).
  
• Tsai-Ching Lu, Marek J. Druzdzel:
  Causal Models, Value of Intervention, and Search for Opportunities.
  
• Peter J. F. Lucas:
  Restricted Bayesian Network Structure Learning.
  
• Irene Martínez, Serafín Moral, Carmelo Rodríguez, Antonio Salmerón:
  Factorisation of Probability Trees and its Application to Inference in Bayesian Networks.
  
• Serafín Moral, Rafael Rumí, Antonio Salmerón:
  Estimating Mixtures of Truncated Exponentials from Data.
  
• José Manuel Peña, José Antonio Lozano, Pedro Larrañaga:
  Unsupervised Learning of Bayesian Networks Via Estimation of Distribution Algorithms.
  
• Roberto O. Puch, Jim Q. Smith, Concha Bielza:
  Inferentially Efficient Propagation in Non-Decomposable Bayesian Network with Hierarchical Junction Trees.
  
• Milan Studený:
  Characterization of Essential Graphs by Means of an Operation of Legal Component Merging.
  
• Miguel A. Virto, Jacinto Martín, David Ríos Insua, Arminda Moreno-Díaz:
  Approximate Solutions of Complex Influence Diagrams through MCMC Methods.
  
• Jirí Vomlel:
  Bayesian Networks in Educational Testing.
  
• Marta Vomlelová, Finn Verner Jensen:
  An Extension of Lazy Evaluation for Influence Diagrams Avoiding Redundant Variables in the Potentials.
  
• Y. Xiang, X. Chen:
  Cooperative Verification of Agent Interface.
  
• Yusuf Kenan Yilmaz, Ethem Alpaydin, H. Levent Akin, Taner Bilgiç:
  Handling of Deterministic Relationships in Constraint-based Causal Discovery.
  
• Frank Jensen, Uffe Kjærulff, Michael Lang, Anders L. Madsen:
  Hugin - The Tool for Bayesian Networks and Influence Diagrams.
  
• Elvira: An Environment for Creating and Using Probabilistic Graphical Models.