In this paper, we investigate a new machine learning framework called Online Transfer Learning (OTL) that aims to transfer knowledge from some source domain to an online learning ...
Discovering common objects that appear frequently in a number of images is a challenging problem, due to (1) the appearance variations of the same common object and (2) the enormo...
With ever increasing computing power, it is possible to process ever more complex fluid simulations. However, a gap between data set sizes and our ability to visualize them remain...
Tony McLoughlin, Robert S. Laramee, Ronald Peikert...
Abstract We present a new margin-based approach to first-order rule learning. The approach addresses many of the prominent challenges in first-order rule learning, such as the comp...
Control of mobile networks raises fundamental and novel problems in controlling the structure of the resulting dynamic graphs. In particular, in applications involving mobile senso...