Inductive learning of first-order theory based on examples has serious bottleneck in the enormous hypothesis search space needed, making existing learning approaches perform poorl...
A structured approach to parallel programming allows to construct applications by composing skeletons, i.e., recurring patterns of task- and data-parallelism. First academic and co...
We consider the problem of estimating CPU (distance computations) and I/O costs for processing range and k-nearest neighbors queries over metric spaces. Unlike the specific case ...
Many approaches to active learning involve periodically training one classifier and choosing data points with the lowest confidence. An alternative approach is to periodically cho...
Preference learning is a challenging problem that involves the prediction of complex structures, such as weak or partial order relations, rather than single values. In the recent ...