Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
This paper will look at the human predisposition to oral tradition and its effectiveness as a learning tool to convey mission-critical information. After exploring the effectivenes...
We present a novel representation of cyclic human locomotion based on a set of spatio-temporal curves of tracked points on the surface of a person. We start by extracting a set of...
Bayesian networks with mixtures of truncated exponentials (MTEs) support efficient inference algorithms and provide a flexible way of modeling hybrid domains (domains containing ...
Helge Langseth, Thomas D. Nielsen, Rafael Rum&iacu...
One of the open problems listed in Rivest and Schapire, 1989] is whether and how that the copies of L in their algorithm can be combined into one for better performance. This pape...