In many real-world classification problems the input contains a large number of potentially irrelevant features. This paper proposes a new Bayesian framework for determining the r...
Yuan (Alan) Qi, Thomas P. Minka, Rosalind W. Picar...
Abstract. The manual acquisition and modeling of tourist information as e.g. addresses of points of interest is time and, therefore, cost intensive. Furthermore, the encoded inform...
In this paper, we propose an autonomous learning scheme to automatically build visual semantic concept models from the output data of Internet search engines without any manual la...
Abstract. We consider the question of protecting the privacy of customers buying digital goods. More specifically, our goal is to allow a buyer to purchase digital goods from a ve...
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...