We propose a distance phrase reordering model (DPR) for statistical machine translation (SMT), where the aim is to learn the grammatical rules and context dependent changes using ...
The MILAN project, a joint effort involving Arizona State University and New York University, has produced and validated fundamental techniques for the realization of efficient, r...
We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepa...
In this poster, we will propose a framework for finding, recommending and inserting learning objects in a digital repository level, exploiting the user context that is captured fro...
This paper proposes a general framework to develop SCORM compliant courses that provide adaptation according to user learning style. The SCORM standard as well as some of the most...