We present a unified framework for reasoning about worst-case regret bounds for learning algorithms. This framework is based on the theory of duality of convex functions. It brin...
Construction of complex software systems with largely off-the-shelf components has become a reality with the wide availability and acceptance of component frameworks and distribut...
William J. McIver Jr., Karim Keddara, Christian Oc...
After two decades of research on automated discovery, many principles are shaping up as a foundation of discovery science. In this paper we view discovery science as automation of ...
Object-oriented programming techniques have been used with great success for some time. But the techniques of object-oriented programming have been largely confined to the single a...
The recent improvements in workstation and interconnection network performance have popularized the clusters of off-the-shelf workstations. However, the usefulness of these cluste...