Abstract. Deep Neural Networks (DNN) propose a new and efficient ML architecture based on the layer-wise building of several representation layers. A critical issue for DNNs remain...
In this paper we propose a data intensive approach for inferring sentence-internal temporal relations. Temporal inference is relevant for practical NLP applications which either e...
This paper presents an approach for educators to evaluate student progress throughout a course, and not merely based on a final exam. We introduce progress reports and describe ho...
We show how to derive time implicit formulations of relaxation schemes for the Euler equations for real materials in several space dimensions. In the fully time explicit setting, t...
In this paper, we propose a mechanism that supports the high quality streaming and adaptation of stored, constant-quality video across best-effort networks. The difficulty in the d...