Factored representations, model-based learning, and hierarchies are well-studied techniques for improving the learning efficiency of reinforcement-learning algorithms in large-sca...
Carlos Diuk, Alexander L. Strehl, Michael L. Littm...
Particle filtering is an effective sequential Monte Carlo approach to solve the recursive Bayesian filtering problem in non-linear and non-Gaussian systems. The algorithm is base...
We present parallel algorithms for processing, extracting and rendering adaptively sampled regular terrain datasets represented as a multiresolution model defined by a super-squa...
The development of precise definitions of security for encryption, as well as a detailed understanding of their relationships, has been a major area of research in modern cryptogr...
Finite Element methods are well suited to the computation of the light distribution in mostly diffuse scenes, but the resulting mesh is often far from optimal to accurately represe...
Annette Scheel, Marc Stamminger, Hans-Peter Seidel