approximate inferenceの例文
- Due to the complexity of the model and the interrelations of predicted variables the process of prediction using a trained model and of training itself is often computationally infeasible and approximate inference and learning methods are used.
- Although theoretically solving an Integer Linear Program is exponential in the size of the decision problem, in practice using state-of-the-art solvers and approximate inference techniques large scale problems can be solved efficiently.
- At about the same time, Dan Roth proved that exact inference in Bayesian networks is in fact # P-complete ( and thus as hard as counting the number of satisfying assignments of a CNF formula ) and that approximate inference, even for Bayesian networks with restricted architecture, is NP-hard.
- His work includes early visual processing of Saliency and Grouping mechanisms, Visual Recognition and Learning, Image Synthesis for Animation and Graphics, theory of Computer Vision in the areas of multiple-view geometry and multi-view tensors, multilinear algebraic systems in Vision and Learning and primal / dual optimization for approximate inference in MRF and Graphical models and recently on deep layered networks.
