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» Generalized loopy 2U: A new algorithm for approximate infere...
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UAI
2003
13 years 6 months ago
Approximate Inference and Constrained Optimization
Loopy and generalized belief propagation are popular algorithms for approximate inference in Markov random fields and Bayesian networks. Fixed points of these algorithms correspo...
Tom Heskes, Kees Albers, Bert Kappen
AAAI
2010
13 years 7 months ago
Efficient Belief Propagation for Utility Maximization and Repeated Inference
Many problems require repeated inference on probabilistic graphical models, with different values for evidence variables or other changes. Examples of such problems include utilit...
Aniruddh Nath, Pedro Domingos
UAI
2008
13 years 6 months ago
Strategy Selection in Influence Diagrams using Imprecise Probabilities
This paper describes a new algorithm to solve the decision making problem in Influence Diagrams based on algorithms for credal networks. Decision nodes are associated to imprecise...
Cassio Polpo de Campos, Qiang Ji
CVPR
2010
IEEE
13 years 8 months ago
Ray Markov Random Fields for Image-Based 3D Modeling: Model and Efficient Inference
In this paper, we present an approach to multi-view image-based 3D reconstruction by statistically inversing the ray-tracing based image generation process. The proposed algorithm...
Shubao Liu, David Cooper
JAIR
2006
143views more  JAIR 2006»
13 years 5 months ago
Convexity Arguments for Efficient Minimization of the Bethe and Kikuchi Free Energies
Loopy and generalized belief propagation are popular algorithms for approximate inference in Markov random fields and Bayesian networks. Fixed points of these algorithms have been...
Tom Heskes