We describe a method for computing closed sets with data-dependent constraints. Especially, we show how the method can be adapted to find frequent closed sets in a given data set...
We present an ensemble learning approach that achieves accurate predictions from arbitrarily partitioned data. The partitions come from the distributed processing requirements of ...
Larry Shoemaker, Robert E. Banfield, Lawrence O. H...
Abstract Steph Durocher∗ and David Kirkpatrick† Department of Computer Science, University of British Columbia Vancouver BC, Canada Given a set of client positions as input, f...
This paper is a continuation of the study of topological properties of omega context free languages (-CFL). We proved in [Topological Properties of Omega Context Free Languages, T...
The question of nonemptiness of the intersection of a nested sequence of closed sets is fundamental in a number of important optimization topics, including the existence of optima...