Empirical risk minimization offers well-known learning guarantees when training and test data come from the same domain. In the real world, though, we often wish to adapt a classi...
John Blitzer, Koby Crammer, Alex Kulesza, Fernando...
Abstract. This paper deals with the issue of learning in multi-agent systems (MAS). Particularly, we are interested in BDI (Belief, Desire, Intention) agents. Despite the relevance...
This paper argues for a return to fundamentals as we enter the new millennium. It argues that the field of Information Systems should no longer be distracted from its natural locu...
Despite substantial improvements in the last few years in software engineering and collaboration tools, coordination in large-scale software development continues to be problemati...
J. Alberto Espinosa, Robert E. Kraut, F. Javier Le...
Role-limiting approaches using explicit theories of problem-solving have been successful for acquiring knowledge from domain experts1 . However most systems using this approach do...