This paper describes a novel approach to the semantic relation detection problem. Instead of relying only on the training instances for a new relation, we leverage the knowledge l...
Chang Wang, James Fan, Aditya Kalyanpur, David Gon...
We describe a method of representing human activities that allows a collection of motions to be queried without examples, using a simple and effective query language. Our approach...
Abstract. Accurately modeling and predicting performance for largescale applications becomes increasingly difficult as system complexity scales dramatically. Analytic predictive mo...
Engin Ipek, Bronis R. de Supinski, Martin Schulz, ...
With the exponential growth of complete genome sequences, the analysis of these sequences is becoming a powerful approach to build genome-scale metabolic models. These models can ...
Skewed distributions appear very often in practice. Unfortunately, the traditional Zipf distribution often fails to model them well. In this paper, we propose a new probability di...