We present an algorithm for fast posterior inference in penalized high-dimensional state-space models, suitable in the case where a few measurements are taken in each time step. W...
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...
We study the problem of learning a group of principal tasks using a group of auxiliary tasks, unrelated to the principal ones. In many applications, joint learning of unrelated ta...
Bernardino Romera-Paredes, Andreas Argyriou, Nadia...
—Recent advances in cognitive radio (CR) technology have brought about a number of wireless standards that support opportunistic access to available white-space spectrum. Address...
Abstract—This paper considers a novel distributed system for collaborative location-based information generation and sharing which become increasingly popular due to the explosiv...