In this paper, we discuss round robin classification (aka pairwise classification), a technique for handling multi-class problems with binary classifiers by learning one classifie...
We extend the VC theory of statistical learning to data dependent spaces of classifiers. This theory can be viewed as a decomposition of classifier design into two components; the...
Adam Cannon, J. Mark Ettinger, Don R. Hush, Clint ...
In this paper, we present a framework for a robotic system with the ability to perform real-world manipulation tasks. The complexity of such tasks determines the precision and fre...
Danica Kragic, Lars Petersson, Henrik I. Christens...
Interactions within a protein structure and interactions between proteins in an assembly are essential considerations in understanding molecular basis of stability and functions o...
In this paper, we shall address the issue of semantic extraction of different regions of interest. The proposed approach is based on statistical methods and models inspired from l...