RRL is a relational reinforcement learning system based on Q-learning in relational state-action spaces. It aims to enable agents to learn how to act in an environment that has no ...
This paper addresses two image sequence analysis issues under a common framework. These tasks are, "rst, motion-based segmentation and second, updating and tracking over time...
—This paper describes a new approach to matching geometric structure in 2D point-sets. The novel feature is to unify the tasks of estimating transformation geometry and identifyi...
We present a new approach to matching graphs embedded in R2 or R3 . Unlike earlier methods, our approach does not rely on the similarity of local appearance features, does not req...
Eduard Serradell, Przemyslaw Glowacki, Jan Kybic, ...
—In this contribution, duals of fountain codes are introduced and their use for lossy source compression is investigated. It is shown both theoretically and experimentally that t...
Dino Sejdinovic, Robert J. Piechocki, Angela Doufe...