Preliminary Program
Wednesday 17/9
9-10.30 Learning
Large incomplete sample robustness in Bayesian networks
Jim Smith1 and Alireza Daneshkhah2
1University of Warwick, Uk, 2Strathclyde University, UK
Factorized Normalized Maximum Likelihood Criterion for Learning Bayesian Network Structures
Tomi Silander, Teemu Roos, Petri Kontkanen, Petri Myllymäki
University of Helsinki
Logical Properties of Stable Conditional Independence
Mathias Niepert and Dirk Van Gucht
Indiana University
11.00-12.30 Learning
Structural-EM for Learning PDG Models from Incomplete Data
Jens Nielsen1, Rafael Rumí2, Antonio Salmerón2
1Universidad de Castilla-La Mancha, 2Universidad de Almería
A Geometric Approach to Learning BN Structures
Milan Studeny and Jiri Vomlel
Institute of Information Theory and Automation of the ASCR
Robust Classification Using Mixtures of Dependency Networks
Jose A. Gamez1, Juan L. Mateo1, Thomas D. Nielsen2, Jose M. Puerta1
1University of Castilla-La Mancha, 2Aalborg University
15.00-16.00 Inference
Policy Explanation in Factored Markov Decision Processes
Francisco Elizalde1, Enrique Sucar2, Manuel Luque3, Javier Díez3, Alberto Reyes1
1IIE, 2INAOE, 3UNED
Approximate representation of optimal strategies from influence diagrams
Finn Verner Jensen
Aalborg University
16.30-17.30 Parameter estimation
Parameter Estimation in Mixtures of Truncated Exponentials
Helge Langseth1, Thomas D. Nielsen2, Rafael Rumí3, Antonio Salmeron3
1The Norwegian University of Science and Technology,
2Aalborg University,
3University of Almeria
Discrimination and its sensitivity in probabilistic networks
Silja Renooij and Linda C. van der Gaag
Utrecht University
Thursday 18/9
9.00-10.30 Multi-agent systems
An Influence Diagram Framework for acting under influence by agents with unknown goals
Nicolaj Søndberg-Jeppesen and Finn Verner Jensen
Aalborg University
Tightly and Loosely Coupled Decision Paradigms in Multiagent Expedition
Yang Xiang and Franklin Hanshar
University of Guelph
Spotlight presentations
11.00-12.30 Modeling
Bayesian Networks: the Quantitative Parental Synergy
Janneke H. Bolt
Utrecht University
Arithmetic circuits of the noisy-or models
Jirka Vomlel and Petr Savicky
Academy of Sciences of the Czech Republic
Spotlight presentations
16.00-19.00 Poster session
An anytime algorithm for evaluating unconstrained influence diagrams
Manuel Luque1, Thomas D. Nielsen2, Finn V. Jensen2
1Departmento Inteligencia Artificial, UNED, 2Aalborg University
Solving CLQG Influence Diagrams Using Arc-Reversal
Anders Madsen
HUGIN EXPERT
Perturbing a set of inaccuracies parameters in Gaussian Bayesian networks
Rosario Susi, Miguel A. Gómez-Villegas, Paloma Main
Universidad Complutense de Madrid
The Probabilistic Interpretation of Model-based Diagnosis
Ildiko Flesch1 and Peter Lucas2
1University of Maastricht, 2Radboud University Nijmegen
Towards consistency in general dependency networks
José A. Gámez, Juan L. Mateo, José M. Puerta
University of Castilla-La Mancha
A* Wars: The Fight for Improving A* Search for Troubleshooting with Dependent Actions
Thorsten J. Ottosen and Finn V. Jensen
Department of Computer Science, Aalborg University, Denmark
Marginals of DAG-isomorphic Independence Models
Peter R. de Waal
Universiteit Utrecht
Complexity Results for Enumerating MPE and Partial MAP
Johan Kwisthout
Utrecht University
Computing the Multinomial Stochastic Complexity in Sub-Linear Time
Tommi Mononen and Petri Myllymäki
Helsinki Institute for Information Technology
Eliciting expert beliefs on the structure of a Bayesian Network
Federico M. Stefanini
Department of Statistics "G.Parenti", University of Florence
Efficient Bayesian Network Learning Using Pairwise Deletion
Olivier Francois
University of Reading
Carmen: An open source project for probabilistic graphical models
Manuel Arias and Francisco Javier Diez
UNED
High-dimensional probability density estimation with randomized ensembles of tree structured Bayesian networks
Sourour Ammar1, Philippe Leray1, Boris Defourny2, Louis Wehenkel2
1LINA, Univ. Nantes, France, 2DEECS & GIGA-R, Univ. Liège, Belgium
A Bayesian approach to estimate probabilities in classification trees
Andrés Cano, Andrés Masegosa, Serafín Moral
University of Granada
A novel scalable and correct Markov boundary learning algorithms under faithfulness condition
Sergio Rodrigues de Morais1 and Alex Aussem2
1INSA-Lyon, LIESP, 2Université de Lyon 1, LIESP
Attribute Clustering Based on Heuristic Tree Partition
Jorge Cordero Hernandez and Yifeng Zeng
Aalborg University
An ICI Model for Opposing Influences
Paul Maaskant1 and Marek Druzdzel2
1Delft University of Technology, 2University of Pittsburgh
Query-based Diagnostics
John Mark Agosta1, Tom Gardos1, Marek Druzdzel2
1Intel Research, 2University of Pittsburgh
Measuring Efficiency in Influence Diagram Models
Barry Cobb
Virginia Military Institute
Friday 19/9
9.00-10.30 Inference
An empirical analysis of loopy belief propagation in three topologies: grids, small-world networks and random graphs
Roberto Santana, Alexander Mendiburu, Jose A. Lozano
The University of the Basque Country
Generalized Loopy 2U: A New Algorithm for Approximate Inference in Credal Networks
Alessandro Antonucci, Marco Zaffalon, Yi Sun, Cassio P. de Campos
IDSIA, Switzerland
New Methods for Marginalization in Lazy Propagation
Anders Madsen
HUGIN EXPERT
11.00-12.30 Learning
Learning naive Bayes regression models from missing data using mixtures of truncated exponentials
Antonio Fernández1, Jens D. Nielsen2, Antonio Salmerón1
1University of Almería, 2University of Castilla-La Mancha
Efficient Model Evaluation in the Search-Based Approach to Latent Structure Discovery
Tao Chen, Nevin L. Zhang, Yi Wang
HKUST
A Score Based Ranking of the Edges for the PC Algorithm
Andres Cano, Manuel Gomez-Olmedo, Serafín Moral
Universidad de Granada