In this paper, we describe a search procedure for statistical machine translation (MT) based on dynmnic programming (DP). Starting from a DP-based solution to the traveling salesm...
In order to scale with modern processors, planning algorithms must become multi-threaded. In this paper, we present parallel shared-memory algorithms for two problems that underli...
Reinforcement learning is an effective machine learning paradigm in domains represented by compact and discrete state-action spaces. In high-dimensional and continuous domains, ti...
Thing-oriented programming (TP) is an emerging programming model which overcomes some of the limitations of current practice in software development in general and of object-orient...
Abstract. Dynamic program optimization is the only recourse for optimizing compilers when machine and program parameters necessary for applying an optimization technique are unknow...