Various ways for decision making with imprecise probabilities—admissibility, maximal expected utility, maximality, E-admissibility, Γ-maximax, Γ-maximin, all of which are well...
Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world proble...
Recently, many global stereo methods have achieved good results by modeling a disparity surface as a Markov random field (MRF) and by solving an optimization problem with various ...
Abstract—A general variational framework for image approximation and segmentation is introduced. By using a continuous “line-process” to represent edge boundaries, it is poss...
In the last few years, several new algorithms based on graph cuts have been developed to solve energy minimization problems in computer vision. Each of these techniques constructs...