The vast amount of information freely available on the Web constitutes a unparalleled resource for the automatic knoweledge discovery and learning. In this paper we propose a study...
Abstract. In the multiagent meeting scheduling problem, agents negotiate with each other on behalf of their users to schedule meetings. While a number of negotiation approaches hav...
We present a general approach to model selection and regularization that exploits unlabeled data to adaptively control hypothesis complexity in supervised learning tasks. The idea ...
As ever-larger training sets for learning to rank are created, scalability of learning has become increasingly important to achieving continuing improvements in ranking accuracy [...
As many real-world problems involve user preferences, costs, or probabilities, constraint satisfaction has been extended to optimization by generalizing hard constraints to soft co...