We address the problem of the combination of multiple data partitions, that we call a clustering ensemble. We use a recent clustering approach, known as Spectral Clustering, and th...
An ensemble of classifiers is a set of classifiers whose predictions are combined in some way to classify new instances. Early research has shown that, in general, an ensemble of ...
In this paper we extend the applicability of our combination method for decision procedures for the word problem to theories sharing non-collapse-free constructors. This extension ...
Recently researchers have introduced methods to develop reusable knowledge in reinforcement learning (RL). In this paper, we define simple principles to combine skills in reinforce...
We present a combination method for generating interpolants for a class of first-order theories. Using interpolant-generation procedures for individual theories as black-boxes, our...