This paper presents two local methods for the control of discrete-time unknown nonlinear dynamical systems, when only a limited amount of input-output data is available. The modeli...
We present a method to classify and localize human actions in video using a Hough transform voting framework. Random trees are trained to learn a mapping between densely-sampled f...
As opposed to traditional supervised learning, multiple-instance learning concerns the problem of classifying a bag of instances, given bags that are labeled by a teacher as being...
Graph Languages1 emerged during the seventies from the necessity to process data structures with complex interrelations. Nowadays, various variants of these languages can be found...
Abstract. Learning in the context of constraint solving is a technique by which previously unknown constraints are uncovered during search and used to speed up subsequent search. R...
Ian P. Gent, Christopher Jefferson, Lars Kotthoff,...