We use machine learners trained on a combination of acoustic confidence and pragmatic plausibility features computed from dialogue context to predict the accuracy of incoming n-be...
Modern high-performance architectures require extremely accurate branch prediction to overcome the performance limitations of conditional branches. We present a framework that cat...
In this paper, we investigate the hypothesis that plan recognition can significantly improve the performance of a casebased reinforcement learner in an adversarial action selectio...
Geography and social relationships are inextricably intertwined; the people we interact with on a daily basis almost always live near us. As people spend more time online, data re...
Abstract— This paper develops a novel mechanism for managing the performance and feasibility trade off withing predictive control. Specifically, it demonstrates that the potenti...