In this paper, we propose a new approach to model-driven development, which we call introspective model-driven development (IMDD). This approach relies heavily on some well-underst...
Context trees are a popular and effective tool for tasks such as compression, sequential prediction, and language modeling. We present an algebraic perspective of context trees for...
Harald Ganzinger, Robert Nieuwenhuis, Pilar Nivela
This paper describes work in progress to develop a standard for interoperability among high-performance scientific components. This research stems from growing recognition that th...
Robert C. Armstrong, Dennis Gannon, Al Geist, Kata...
This paper explores the challenge of scaling up language processing algorithms to increasingly large datasets. While cluster computing has been available in commercial environment...
We present a framework where auxiliary MT systems are used to provide lexical predictions to a main SMT system. In this work, predictions are obtained by means of pivoting via aux...