Abstract— This paper describes a novel approach for incremental learning of human motion pattern primitives through on-line observation of human motion. The observed motion time ...
We present a concept to use off-line learning approaches to achieve on-line learning of cooperative behavior of agents and instantiate this concept for evolutionary learning with ...
Most data mining algorithms assume static behavior of the incoming data. In the real world, the situation is different and most continuously collected data streams are generated by...
Lior Cohen, Gil Avrahami, Mark Last, Abraham Kande...
RELIEF is considered one of the most successful algorithms for assessing the quality of features. In this paper, we propose a set of new feature weighting algorithms that perform s...
We study on-line decision problems where the set of actions that are available to the decision algorithm vary over time. With a few notable exceptions, such problems remained larg...
Robert D. Kleinberg, Alexandru Niculescu-Mizil, Yo...