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Speeding-up Graphical Model Optimization via a Coarse-to-fine Cascade of Pruning Classifiers
The proposed approach relies on a multi-scale pruning scheme that is able to progressively reduce the solution space by use of a novel strategy based on a coarse-to-fine cascade of learnt classifiers.
A Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems
However, on new and challenging types of models our findings disagree and suggest that polyhedral methods and integer programming solvers are competitive in terms of runtime and solution quality over a large range of model types.
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