We target the problem of closed-loop learning of control policies that map visual percepts to continuous actions. Our algorithm, called Reinforcement Learning of Joint Classes (RLJ...
Reliable detection of fiducial targets in real-world images is addressed in this paper. We show that even the best existing schemes are fragile when exposed to other than laborator...
We address the problem of incorporating user preference in automatic image enhancement. Unlike generic tools for automatically enhancing images, we seek to develop methods that ca...
Monaural speech segregation in reverberant environments is a very difficult problem. We develop a supervised learning approach by proposing an objective function that directly rel...
In this paper, we study multi-agent economic systems using a recent approach to economic modeling called Agent-based Computational Economics (ACE): the application of the Complex ...