In a principal-agent problem, a principal seeks to motivate an agent to take a certain action beneficial to the principal, while spending as little as possible on the reward. This...
In this paper, we compare both discriminative and generative parameter learning on both discriminatively and generatively structured Bayesian network classifiers. We use either ma...
We present several new algorithms for multiagent reinforcement learning. A common feature of these algorithms is a parameterized, structured representation of a policy or value fu...
Carlos Guestrin, Michail G. Lagoudakis, Ronald Par...
Three-dimensional rotational angiography (3D-RA) is a relatively new and promising technique for imaging blood vessels. In this paper, we propose a novel 3D-RA vascular segmentati...
Rui Gan, Albert C. S. Chung, Wilbur C. K. Wong, Si...
Fourier-based forward and back-projection methods have the potential to reduce computation demands in iterative tomographic image reconstruction. Interpolation errors are a limita...