How much can randomness help computation? Motivated by this general question and by volume computation, one of the few instances where randomness provably helps, we analyze a noti...
This study addresses the problem of unsupervised visual learning. It examines existing popular model order selection criteria before proposes two novel criteria for improving visu...
This paper explores unexpected results that lie at the intersection of two common themes in the KDD community: large datasets and the goal of building compact models. Experiments ...
ABSTRACT. This paper investigates the problem of finding subclasses of nonmonotonic reasoning which can be implemented efficiently. The ability to "define" propositions u...
Abstract. We present Shekoosh, a novel framework for constraint-based generation of structurally complex inputs of large sizes. Given a Java predicate that represents the desired s...