Model learning and tracking are two important topics in computer vision. While there are many applications where one of them is used to support the other, there are currently only...
We consider the problem of multi-task learning, that is, learning multiple related functions. Our approach is based on a hierarchical Bayesian framework, that exploits the equival...
In this paper, a statistical learning approach to spatial context exploitation for semantic image analysis is presented. The proposed method constitutes an extension of the key pa...
We describe a novel framework developed for transfer learning within reinforcement learning (RL) problems. Then we exhibit how this framework can be extended to intelligent tutorin...
Kimberly Ferguson, Beverly Park Woolf, Sridhar Mah...
Our goal is to provide learning mechanisms to game agents so they are capable of adapting to new behaviors based on the actions of other agents. We introduce a new on-line reinfor...