Meta-Learning has been successfully applied to acquire knowledge used to support the selection of learning algorithms. Each training example in Meta-Learning (i.e. each meta-exampl...
This paper describes a novel application of Statistical Learning Theory (SLT) to control model complexity in flow estimation. SLT provides analytical generalization bounds suitabl...
Zoran Duric, Fayin Li, Harry Wechsler, Vladimir Ch...
Abstract Multi-agent simulation is applied to explore how different types of task variety cause workgroups to change their task allocation accordingly. We studied two groups, gener...
We describe and analyze an algorithmic framework for online classification where each online trial consists of multiple prediction tasks that are tied together. We tackle the prob...
The TaskTracer system seeks to help multi-tasking users manage the resources that they create and access while carrying out their work activities. It does this by associating with...
Jianqiang Shen, Lida Li, Thomas G. Dietterich, Jon...