In this paper, we propose a novel metric learning method based on regularized moving least squares. Unlike most previous metric learning methods which learn a global Mahalanobis d...
Input feature ranking and selection represent a necessary preprocessing stage in classification, especially when one is required to manage large quantities of data. We introduce a ...
—Mining temporal network models from discrete event streams is an important problem with applications in computational neuroscience, physical plant diagnostics, and human-compute...
We present a generic natural language processing (NLP) architecture, acronym QTIL, based on a system of cooperating multiple agents (Q/A, T, I, and L agents) which can be used in ...
This paper proposes a hybrid approach for managing knowledge within companies based on communication between people. In addition to traditional Knowledge Management Systems our co...
Robert Loew, Katrin Kuemmel, Judith Ruprecht, Udo ...