This paper presents a header compression algorithm that unlike previous protocols is capable of compressing MAC headers in a multiple-access (shared) channel. Previous schemes coul...
We develop a probabilistic criterion for belief expansion that is sensitive to the degree of contextual fit of the new information to our belief set as well as to the reliability...
Abstract. We propose a new approach to collaborative filtering in mobile tourist information systems based on spatio-temporal proximity in social contexts. Users store ratings and ...
Alexandre de Spindler, Moira C. Norrie, Michael Gr...
In this paper, we describe a computational system that generates story analogues based on previous stories. Unlike many previous works on story generation that attempt to produce ...
Contextual bandit learning is a reinforcement learning problem where the learner repeatedly receives a set of features (context), takes an action and receives a reward based on th...