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Probabilistic Graphical Models

7th European Workshop, PGM 2014, Utrecht, The Netherlands, September 17-19, 2014. Proceedings

  • Conference proceedings
  • © 2014

Overview

Editors:
  1. Linda C. Gaag

    1. Utrecht University, Faculty of Science, Department of Information and Computing Sciences, Princetonplein 5, 3584 CC Utrecht, The Netherlands

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  2. Ad J. Feelders

    1. Utrecht University, Faculty of Science, Department of Information and Computing Sciences, Princetonplein 5, 3584 CC Utrecht,, The Netherlands

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 8754)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: PGM 2014.

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About this book

This book constitutes the refereed proceedings of the 7th International Workshop on Probabilistic Graphical Models, PGM 2014, held in Utrecht, The Netherlands, in September 2014. The 38 revised full papers presented in this book were carefully reviewed and selected from 44 submissions. The papers cover all aspects of graphical models for probabilistic reasoning, decision making, and learning.

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Table of contents (38 papers)

  1. Front Matter

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  2. Structural Sensitivity for the Knowledge Engineering of Bayesian Networks

    • David Albrecht, Ann E. Nicholson, Chris Whittle
    Pages 1-16

  3. A Pairwise Class Interaction Framework for Multilabel Classification

    • Jacinto Arias, José A. Gámez, Thomas D. Nielsen, José M. Puerta
    Pages 17-32

  4. From Information to Evidence in a Bayesian Network

    • Ali Ben Mrad, Véronique Delcroix, Sylvain Piechowiak, Philip Leicester
    Pages 33-48

  5. Learning Gated Bayesian Networks for Algorithmic Trading

    • Marcus Bendtsen, Jose M. Peña
    Pages 49-64

  6. Local Sensitivity of Bayesian Networks to Multiple Simultaneous Parameter Shifts

    • Janneke H. Bolt, Silja Renooij
    Pages 65-80

  7. Bayesian Network Inference Using Marginal Trees

    • Cory J. Butz, Jhonatan de S. Oliveira, Anders L. Madsen
    Pages 81-96

  8. On SPI-Lazy Evaluation of Influence Diagrams

    • Rafael Cabañas, Andrés Cano, Manuel Gómez-Olmedo, Anders L. Madsen
    Pages 97-112

  9. Extended Probability Trees for Probabilistic Graphical Models

    • Andrés Cano, Manuel Gómez-Olmedo, Serafín Moral, Cora B. Pérez-Ariza
    Pages 113-128

  10. Mixture of Polynomials Probability Distributions for Grouped Sample Data

    • Barry R. Cobb
    Pages 129-144

  11. Trading off Speed and Accuracy in Multilabel Classification

    • Giorgio Corani, Alessandro Antonucci, Denis D. Mauá, Sandra Gabaglio
    Pages 145-159

  12. Robustifying the Viterbi Algorithm

    • Cedric De Boom, Jasper De Bock, Arthur Van Camp, Gert de Cooman
    Pages 160-175

  13. Extended Tree Augmented Naive Classifier

    • Cassio P. de Campos, Marco Cuccu, Giorgio Corani, Marco Zaffalon
    Pages 176-189

  14. Evaluation of Rules for Coping with Insufficient Data in Constraint-Based Search Algorithms

    • Martijn de Jongh, Marek J. Druzdzel
    Pages 190-205

  15. Supervised Classification Using Hybrid Probabilistic Decision Graphs

    • Antonio Fernández, Rafael Rumí, José del Sagrado, Antonio Salmerón
    Pages 206-221

  16. Towards a Bayesian Decision Theoretic Analysis of Contextual Effect Modifiers

    • Gabor Hullam, Peter Antal
    Pages 222-237

  17. Discrete Bayesian Network Interpretation of the Cox’s Proportional Hazards Model

    • Jidapa Kraisangka, Marek J. Druzdzel
    Pages 238-253

  18. Minimizing Relative Entropy in Hierarchical Predictive Coding

    • Johan Kwisthout
    Pages 254-270

  19. Treewidth and the Computational Complexity of MAP Approximations

    • Johan Kwisthout
    Pages 271-285

  20. Bayesian Networks with Function Nodes

    • Anders L. Madsen, Frank Jensen, Martin Karlsen, Nicolaj Soendberg-Jeppesen
    Pages 286-301
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Other volumes

  1. Probabilistic Graphical Models

Editors and Affiliations

  • Utrecht University, Faculty of Science, Department of Information and Computing Sciences, Princetonplein 5, 3584 CC Utrecht, The Netherlands

    Linda C. Gaag

  • Utrecht University, Faculty of Science, Department of Information and Computing Sciences, Princetonplein 5, 3584 CC Utrecht,, The Netherlands

    Ad J. Feelders

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