Classifier learning methods commonly assume that the training data consist of randomly drawn examples from the same distribution as the test examples about which the learned model...
—This paper proposes a method of learning a similarity matrix from pairwise constraints for interactive clustering. The similarity matrix can be learned by solving an optimizatio...
— Many calibration methods calibrate a pair of sensors at a time. For robotic systems with many sensors, they are often time-consuming to use, and can also lead to inaccurate res...
We propose a method for local search of Boolean relations relating variables of a CNF formula. The method is to branch on small subsets of the set of CNF variables and to analyze ...
Abstract. This paper presents a method to describe the operational semantics of languages based on their meta-model. We combine the established high-level modelling languages MOF, ...