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PGM 2006: Prague, Czech Republic
- Milan Studený, Jirí Vomlel:
Third European Workshop on Probabilistic Graphical Models, 12-15 September 2006, Prague, Czech Republic. Electronic Proceedings. 2006 - Joaquín Abellán, Manuel Gómez-Olmedo, Serafín Moral:
Some Variations on the PC Algorithm. 1-8 - Peter Antal, András Gézsi, Gábor Hullám, András Millinghoffer:
Learning Complex Bayesian Network Features for Classification. 9-16 - Peter Antal, András Millinghoffer:
Literature Mining using Bayesian Networks. 17-24 - Alessandro Antonucci, Marco Zaffalon:
Locally specified credal networks. 25-34 - Olav Bangsø, N. Sondberg-Madsen, Finn Verner Jensen:
A Bayesian Network Framework for the Construction of Virtual Agents with Human-like Behaviour. 35-42 - Janneke H. Bolt:
Loopy Propagation: the Convergence Error in Markov Networks. 43-50 - Janneke H. Bolt, Linda C. van der Gaag:
Preprocessing the MAP Problem. 51-58 - Tao Chen, Nevin Lianwen Zhang:
Quartet-Based Learning of Shallow Latent Variables. 59-66 - Barry R. Cobb:
Continuous Decision MTE Influence Diagrams. 67-74 - A. J. Feelders, Jevgenijs Ivanovs:
Discriminative Scoring of Bayesian Network Classifiers: a Comparative Study. 75-82 - M. Julia Flores, José A. Gámez, Serafín Moral:
The Independency tree model: a new approach for clustering and factorisation. 83-90 - Olivier François, Philippe Leray:
Learning the Tree Augmented Naive Bayes Classifier from incomplete datasets. 91-98 - Linda C. van der Gaag, Silja Renooij, Petra L. Geenen:
Lattices for Studying Monotonicity of Bayesian Networks. 99-106 - Linda C. van der Gaag, Peter R. de Waal:
Multi-dimensional Bayesian Network Classifiers. 107-114 - José A. Gámez, Juan L. Mateo, José Miguel Puerta:
Dependency networks based classifiers: learning models by using independence. 115-122 - José A. Gámez, Rafael Rumí, Antonio Salmerón:
Unsupervised naive Bayes for data clustering with mixtures of truncated exponentials. 123-130 - Marcel van Gerven, Francisco Javier Díez:
Selecting Strategies for Infinite-Horizon Dynamic LIMIDS. 131-138 - Miguel Ángel Gómez-Villegas, Paloma Main, Rosario Susi:
Sensitivity analysis of extreme inaccuracies in Gaussian Bayesian Networks. 139-146 - Christophe Gonzales, N. Jouve:
Learning Bayesian Networks Structure using Markov Networks. 147-154 - Patrik O. Hoyer, Shohei Shimizu, Antti J. Kerminen:
Estimation of linear, non-gaussian causal models in the presence of confounding latent variables. 155-162 - Rasa Jurgelenaite, Tom Heskes:
Symmetric Causal Independence Models for Classification. 163-170 - Johan Kwisthout, Gerard Tel:
Complexity Results for Enhanced Qualitative Probabilistic Networks. 171-178 - Manuel Luque, Francisco Javier Díez:
Decision analysis with influence diagrams using Elvira's explanation facilities. 179-186 - Irene Martínez, Carmelo Rodríguez, Antonio Salmerón:
Dynamic importance sampling in Bayesian networks using factorisation of probability trees. 187-194 - Stijn Meganck, Sam Maes, Philippe Leray, Bernard Manderick:
Learning Semi-Markovian Causal Models using Experiments. 195-206 - Jason Morton, Lior Pachter, Anne Shiu, Bernd Sturmfels, Oliver Wienand:
Geometry of rank tests. 207-214 - Jens Dalgaard Nielsen, Manfred Jaeger:
An Empirical Study of Efficiency and Accuracy of Probabilistic Graphical Models. 215-222 - Søren Holbech Nielsen, Thomas D. Nielsen:
Adapting Bayes Network Structures to Non-stationary Domains. 223-230 - Kristian G. Olesen, Ole K. Hejlesen, Ram Dessau, Ivan Beltoft, Michael Trangeled:
Diagnosing Lyme disease - Tailoring patient specific Bayesian networks for temporal reasoning. 231-238 - Demet Özgür-Ünlüakin, Taner Bilgiç:
Predictive Maintenance using Dynamic Probabilistic Networks. 239-246 - José M. Peña, Roland Nilsson, Johan Björkegren, Jesper Tegnér:
Reading Dependencies from the Minimal Undirected Independence Map of a Graphoid that Satisfies Weak Transitivity. 247-254 - Silja Renooij, Linda C. van der Gaag:
Evidence and Scenario Sensitivities in Naive Bayesian Classifiers. 255-262 - Alberto Reyes, Pablo H. Ibargüengoytia, Luis Enrique Sucar, Eduardo F. Morales:
Abstraction and Refinement for Solving Continuous Markov Decision Processes. 263-270 - Guzmán Santafé, José Antonio Lozano, Pedro Larrañaga:
Bayesian Model Averaging of TAN Models for Clustering. 271-278 - Xiaoxun Sun, Marek J. Druzdzel, Changhe Yuan:
Dynamic Weighting A* Search-based MAP Algorithm for Bayesian Networks. 279-286 - Petr Simecek:
A Short Note on Discrete Representability of Independence Models. 287-292 - Peter A. Thwaites, Jim Q. Smith:
Evaluating Causal effects using Chain Event Graphs. 293-300 - Yi Wang, Nevin Lianwen Zhang:
Severity of Local Maxima for the EM Algorithm: Experiences with Hierarchical Latent Class Models. 301-308 - Y. Xiang:
Optimal Design with Design Networks. 309-316 - Changhe Yuan, Marek J. Druzdzel:
Hybrid Loopy Belief Propagation. 317-324 - Adam Zagorecki, Marek J. Druzdzel:
Probabilistic Independence of Causal Influences. 325-332
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