4th Workshop on Algorithmic issues for Inference in Graphical Models - AIGM14 -  September 22, 2014. Paris.

The aim of this workshop is to bridge the gap between Statistics and Artificial Intelligence communities where approximate inference methods for GM are developped. We are primarily interested in algorithmic aspects of probabilistic (e.g. Markov random fields, Bayesian networks, influence diagrams), deterministic (e.g. Constraint Satisfaction Problems, SAT, weighted variants, Generalized Additive Independence models) or hybrid (e.g. Markov logic networks) models. We expect both:

• 1. reviews that analyze similarities and differences betwen approaches developped by computer scientists and statisticians in these areas and

  2. original research works which propose new algorithms and show their performance on data sets as compared to state-of-the-art methods.

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